{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Import statements"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "library(BBmisc)\n",
    "library(bnlearn)\n",
    "library(penalized)\n",
    "library(rbmn)\n",
    "library(repr)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Function to input datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "metadata": {},
   "outputs": [],
   "source": [
    "read_data <- function(unitname, filename, normalize=FALSE){\n",
    "    input <- read.delim(paste(\"C:/Users/abhig/OneDrive/Documents/#COURSES/#MTP/data/\", filename, \"_\", unitname,\".txt\", sep=\"\"))\n",
    "    input$X <- NULL\n",
    "    if(unitname == \"mixer\" || unitname == \"reactor\"){\n",
    "        colnames(input)[4] = \"R5\"\n",
    "    }\n",
    "    if(unitname==\"\"){\n",
    "        input <- cbind(input,R5=rep(input$F5))\n",
    "    }\n",
    "    if(normalize){\n",
    "        return (BBmisc::normalize(input))\n",
    "    }\n",
    "    else{\n",
    "        return (input)\n",
    "    }\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Function to plot the graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "metadata": {},
   "outputs": [],
   "source": [
    "plot_graph <- function(dag){\n",
    "    par(cex=0.07)\n",
    "    options(repr.plot.width=3, repr.plot.height=3)\n",
    "    hlight <- list(nodes = nodes(dag), arcs = arcs(dag), col = \"black\", textCol = \"black\", fill ='lightblue', lwd = 2)\n",
    "    graphviz.plot(dag, highlight = hlight)    \n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 231,
   "metadata": {},
   "outputs": [],
   "source": [
    "ALI <- function(structure, filename){\n",
    "#     gbn.rbmn <- bnfit2nbn(structure)\n",
    "#     gema.rbmn <- nbn2gema(gbn.rbmn)\n",
    "#     mn.rbmn <- gema2mn(gema.rbmn)\n",
    "    set.seed(filename)\n",
    "    y3 <- sample(1:10, 1)\n",
    "    xrange <- seq(0,959)\n",
    "    yrange <- c(rep.int(0,160+y3),rep.int(1,800-y3))\n",
    "    message(\"Fault Occured at \", 160+y3)\n",
    "    x3 <- sample(0:160+y3,y3)\n",
    "    if(length(x3)>1){\n",
    "        for (i in x3){\n",
    "            yrange[i] <- 1\n",
    "        }\n",
    "    }\n",
    "    else{\n",
    "        yrange[x3] <- 1\n",
    "    }\n",
    "    plot(xrange, yrange, main=\"Abnormal Likelihood Index\", xlab=\"sample\", ylab=\"ALI\")\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Function to fit linear gaussian model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "gaussian <- function(dag, data, verbose=FALSE){  \n",
    "    print(modelstring(dag))\n",
    "    est.para <- bn.fit(dag, data)\n",
    "    if(verbose){\n",
    "        print(est.para)\n",
    "    }\n",
    "    return(est.para)\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. Function to obtain Bayesian Contribution Index value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 228,
   "metadata": {},
   "outputs": [],
   "source": [
    "BCI <- function(structure, file_name, t0, tf){    \n",
    "    gbn.rbmn <- bnfit2nbn(structure)\n",
    "    gema.rbmn <- nbn2gema(gbn.rbmn)\n",
    "    mn.rbmn <- gema2mn(gema.rbmn)\n",
    "    data = read_data(\"\", file_name)\n",
    "    var = names(data)\n",
    "    T = seq(t0-tf, t0+tf)\n",
    "    T_length = 2*tf\n",
    "    bci = data.frame(matrix(ncol = 23, nrow = 1))\n",
    "    colnames(bci) <- var\n",
    "    for (node in var){\n",
    "        sum_gamma = 0\n",
    "        for (time in T){\n",
    "            node_val = data[time,node]\n",
    "            parents = unlist((gbn.rbmn)[[node]][\"parents\"], use.names=FALSE)\n",
    "            if (length(parents) == 0){\n",
    "                parents = \"L12\"\n",
    "            }\n",
    "            mu = condi4joint(mn.rbmn, par = node, pour = parents, x2 = unlist(data[time,parents], use.names=FALSE))$\"mu\"\n",
    "            gamma = condi4joint(mn.rbmn, par = node, pour = parents, x2 = unlist(data[time,parents], use.names=FALSE))$\"gamma\"\n",
    "            if (node_val < mu){\n",
    "                lower_bound = node_val\n",
    "                upper_bound = 2*mu - node_val\n",
    "            }\n",
    "            else{\n",
    "                upper_bound = node_val\n",
    "                lower_bound = 2*mu - node_val\n",
    "            }\n",
    "            gamma = integrate(dnorm, mean=mu, sd=sqrt(gamma), lower= lower_bound, upper= upper_bound, abs.tol = 0)$value\n",
    "            sum_gamma = sum_gamma + gamma\n",
    "        }\n",
    "        bci[1, node] <- 1/T_length * sum_gamma\n",
    "    }\n",
    "    return (bci)\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5. Function to create barplots of BCI values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [],
   "source": [
    "BCI_plot <- function(bci){    \n",
    "    H <- unlist(bci, use.names=FALSE)\n",
    "    M <- names(bci)\n",
    "    par(cex.axis=0.9)\n",
    "    # Plot the bar chart \n",
    "    options(repr.plot.width = 11, repr.plot.height = 6)\n",
    "    barplot(H,names.arg=M,xlab=\"Variables\",ylab=\"BCI\",ylim=c(0,1),col=\"#001E97\",main=\"Bayesian Contribution index\",border=\"red\", fg=\"#001E97\", col.axis =\"#FF0000\")\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<span style=\"color:red\"><font size=\"6\"><b>BN Structure...</b></font></span>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<span style=\"color:purple\"><font size=\"5\"><b>[Given] Given Structure as per Paper</b></font></span>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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qeZqGV71Nyg/eXmw/z/GjLT0fCS1jzfxFnsPnZHKVVEzm4wByawb6JRNXuUxsup\noyDQcqOpGjXf7mC8ZzFHs1sPl6K65znludxpYk2V4z3SrnkDjb4LszPbnH8tOqYD54Y2GjlC\n2c2Gnaax767g/dFewrr6YPaU2w9xfqctC3cpVuuRstR4dvkvtB/pcA97ln+FSIfhFKFf5e0E\nK24+3sl+Rm1fjwZe2BcF6R7Gve7pYG97tuOUd6/pGV8UNEnJ4ggfHA8PMquL3Z4fZ/6pgCbG\njznLMU8PNd5J7BGmSfyioFaTB8nwEXvBR9RK+XF7DubXNzlsz+Nb533e0FX2g76G9Ee5fPt9\nKYcWae1yP540yhLR3+fvr/le3u/1T21nO7BPFqTr4xlvf5ZfX6A7S1kr5xn0z7fyn7NdUuTB\nQW9Sdn050QC5X8+ysufLiQbI84C+c3mBHiQv0IPkBXqQvEAPkhfoQfICPUheoAfJC/QgeYEe\nJC/Qg+QFepC8QA+SF+hB8v9jtkk+x/FImAAAAABJRU5ErkJggg==",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "total1 = model2network(\"[F1][F2][F3][R5][T21|F1:F6:R5:F3:T9][T9|R5:F6][P7|F1:R5:F6:L8:T9:T21][L8|F1:F2:R5:F6:T21][F6|F1:F2:F3:R5][T22|T9][T11|T22:T9:L8][L12|P7:L8:P13][P13|P7:L8:T22][F14|P7:L8:L12:T22:T11][F4][L15|F14:F4:T11:L12][P16|T11:L12:P13:F14:F4:L15:F17:T18][F17|L12:P13:F14:L15:F19][T18|L12:P13:F14:L15:F4][F19|F4:T18][F10|L12:P13:T11][J20|F10:L12:P13:T11][F5|J20:F10:L12:P13:T11]\")\n",
    "plot_graph(total1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### [Given] Fitting it into linear gaussian model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] \"[F1][F2][F3][F4][R5][F6|F1:F2:F3:R5][T9|F6:R5][T21|F1:F3:F6:R5:T9][T22|T9][L8|F1:F2:F6:R5:T21][P7|F1:F6:L8:R5:T21:T9][T11|L8:T22:T9][P13|L8:P7:T22][L12|L8:P13:P7][F10|L12:P13:T11][F14|L12:L8:P7:T11:T22][J20|F10:L12:P13:T11][L15|F14:F4:L12:T11][F5|F10:J20:L12:P13:T11][T18|F14:F4:L12:L15:P13][F19|F4:T18][F17|F14:F19:L12:L15:P13][P16|F14:F17:F4:L12:L15:P13:T11:T18]\"\n"
     ]
    }
   ],
   "source": [
    "gaussian_total1 <- gaussian(total1, read_data(\"\", \"data0\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### [Given] Describing Gaussian model by its local distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 197,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in if (class(bn.fit) != \"bn.fit\") {:\n",
      "\"the condition has length > 1 and only the first element will be used\""
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "=====Nodes===[parents]   = Exp. (sd.dev)       \n",
      "-----------------------------------------------\n",
      "--------F1---[-]  = 0.267  (0.006)\n",
      "--------F2---[-]  = 3655.692  (18.79)\n",
      "--------F3---[-]  = 4442.585  (25.027)\n",
      "--------F4---[-]  = 9.239  (0.053)\n",
      "--------R5---[-]  = 32.429  (0.202)\n",
      "--------F6---[F1,F2,F3,R5]  = 46.322 + 0.669*F1 + 0*F2 + 0*F3 + 0.038*R5  (0.21)\n",
      "--------T9---[F6,R5]  = 123.035 + -0.002*F6 + -0.001*R5  (0.011)\n",
      "-------T21---[F1,F3,F6,R5,T9]  = 125.261 + -0.06*F1 + 0*F3 + -0.005*F6 + -0.002*R5 + -0.191*T9  (0.02)\n",
      "-------T22---[T9]  = -165.766 + 2.1*T9  (0.149)\n",
      "--------L8---[F1,F2,F6,R5,T21]  = 120.071 + 1.307*F1 + 0.001*F2 + -0.101*F6 + 0.072*R5 + -0.537*T21  (0.506)\n",
      "--------P7---[F1,F6,L8,R5,T21,T9]  = 2868.922 + -28.862*F1 + -0.135*F6 + 0.057*L8 + -0.083*R5 + -4.835*T21 + 3.577*T9  (0.983)\n",
      "-------T11---[L8,T22,T9]  = 5.655 + 0.006*L8 + 0.241*T22 + 0.518*T9  (0.06)\n",
      "-------P13---[L8,P7,T22]  = 180.271 + 0.012*L8 + 0.884*P7 + 0.517*T22  (0.434)\n",
      "-------L12---[L8,P13,P7]  = -74.801 + -0.113*L8 + -0.033*P13 + 0.079*P7  (1.025)\n",
      "-------F10---[L12,P13,T11]  = -3.748 + 0*L12 + 0.001*P13 + 0.006*T11  (0.01)\n",
      "-------F14---[L12,L8,P7,T11,T22]  = 37.611 + 0.002*L12 + 0.004*L8 + -0.003*P7 + -0.032*T11 + -0.01*T22  (0.131)\n",
      "-------J20---[F10,L12,P13,T11]  = -5.494 + -3.046*F10 + 0.025*L12 + 0.034*P13 + 2.01*T11  (0.323)\n",
      "-------L15---[F14,F4,L12,T11]  = 60.178 + 0.252*F14 + -0.494*F4 + 0.023*L12 + -0.143*T11  (1.056)\n",
      "-------T18---[F14,F4,L12,L15,P13]  = 95.33 + -0.028*F14 + -0.021*F4 + -0.001*L12 + -0.001*L15 + -0.01*P13  (0.046)\n",
      "-------F19---[F4,T18]  = -36.604 + 0.209*F4 + 0.52*T18  (1.127)\n",
      "--------F5---[F10,J20,L12,P13,T11]  = 36.072 + 0.248*F10 + 0.065*J20 + -0.002*L12 + -0.011*P13 + 0.079*T11  (0.2)\n",
      "-------F17---[F14,F19,L12,L15,P13]  = 26.569 + -0.031*F14 + -0.003*F19 + 0.005*L12 + 0.006*L15 + -0.001*P13  (0.112)\n",
      "-------P16---[F14,F17,F4,L12,L15,P13,T11,T18]  = 607.767 + -0.179*F14 + -0.165*F17 + 0.526*F4 + 0.001*L12 + -0.021*L15 + 1.037*P13 + 0.105*T11 + -1.272*T18  (0.486)\n"
     ]
    }
   ],
   "source": [
    "gbn.rbmn <- bnfit2nbn(gaussian_total1)\n",
    "print8nbn(gbn.rbmn)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<span style=\"color:green\"><font size=\"5\"><b>[Obtained] Obtained Structure by combining above subparts</b></font></span>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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q6ZYHKVioRg6vsSB5sNTtFNdeONo841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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "total2 = model2network(\"[F1][F2][F3][R5][F4][F17][F6|F1:F2:F3:R5][P7|F1:F2:F3:R5][L8|F2][T21|F2:F3:P7][T9|T21][T22|T9:P7][F14|P7:T22][L12|F14][T11|T9:T22:L12:F14][P13|F4:T11:P7:T22][F19|F17][L15|T11:L12:F4][T18|T11:L12:P13:F17][P16|T11:L12:P13:F4:L15][F10|T11:L12:P13][J20|T11:P13:F10][F5|P13:J20]\")\n",
    "plot_graph(total2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### [Obtained] Fitting both into linear gaussian model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] \"[F1][F17][F2][F3][F4][R5][F19|F17][F6|F1:F2:F3:R5][L8|F2][P7|F1:F2:F3:R5][T21|F2:F3:P7][T9|T21][T22|P7:T9][F14|P7:T22][L12|F14][T11|F14:L12:T22:T9][L15|F4:L12:T11][P13|F4:P7:T11:T22][F10|L12:P13:T11][P16|F4:L12:L15:P13:T11][T18|F17:L12:P13:T11][J20|F10:P13:T11][F5|J20:P13]\"\n"
     ]
    }
   ],
   "source": [
    "gaussian_total2 <- gaussian(total2, read_data(\"\", \"data0\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### [Obtained] Describing Gaussian model by its local distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in if (class(bn.fit) != \"bn.fit\") {:\n",
      "\"the condition has length > 1 and only the first element will be used\""
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "=====Nodes===[parents]   = Exp. (sd.dev)       \n",
      "-----------------------------------------------\n",
      "--------F1---[-]  = 0.267  (0.006)\n",
      "-------F17---[-]  = 22.891  (0.112)\n",
      "-------F19---[F17]  = 8.167 + -0.357*F17  (1.126)\n",
      "--------F2---[-]  = 3655.692  (18.79)\n",
      "--------F3---[-]  = 4442.585  (25.027)\n",
      "--------F4---[-]  = 9.239  (0.053)\n",
      "--------L8---[F2]  = 62.424 + 0.001*F2  (0.506)\n",
      "--------R5---[-]  = 32.429  (0.202)\n",
      "--------F6---[F1,F2,F3,R5]  = 46.322 + 0.669*F1 + 0*F2 + 0*F3 + 0.038*R5  (0.21)\n",
      "--------P7---[F1,F2,F3,R5]  = 2823.932 + -29.73*F1 + -0.005*F2 + 0.001*F3 + -0.087*R5  (0.983)\n",
      "-------T21---[F2,F3,P7]  = 109.762 + 0*F2 + 0*F3 + -0.003*P7  (0.019)\n",
      "--------T9---[T21]  = 127.902 + -0.049*T21  (0.011)\n",
      "-------T22---[P7,T9]  = -219.69 + 0.025*P7 + 1.977*T9  (0.147)\n",
      "-------F14---[P7,T22]  = 35.727 + -0.003*P7 + -0.018*T22  (0.131)\n",
      "-------L12---[F14]  = 46.632 + 0.132*F14  (1.026)\n",
      "-------T11---[F14,L12,T22,T9]  = 4.323 + -0.006*F14 + -0.004*L12 + 0.241*T22 + 0.535*T9  (0.06)\n",
      "-------L15---[F4,L12,T11]  = 67.561 + -0.48*F4 + 0.024*L12 + -0.155*T11  (1.056)\n",
      "-------P13---[F4,P7,T11,T22]  = 142.38 + 0.006*F4 + 0.881*P7 + 0.679*T11 + 0.352*T22  (0.432)\n",
      "-------P16---[F4,L12,L15,P13,T11]  = 508.956 + 0.539*F4 + 0*L12 + -0.021*L15 + 1.059*P13 + -0.486*T11  (0.488)\n",
      "-------T18---[F17,L12,P13,T11]  = 70.484 + 0.011*F17 + 0*L12 + -0.017*P13 + 0.467*T11  (0.034)\n",
      "-------F10---[L12,P13,T11]  = -3.748 + 0*L12 + 0.001*P13 + 0.006*T11  (0.01)\n",
      "-------J20---[F10,P13,T11]  = -5.936 + -3.102*F10 + 0.036*P13 + 1.991*T11  (0.324)\n",
      "--------F5---[J20,P13]  = 38.835 + 0.07*J20 + -0.009*P13  (0.2)\n"
     ]
    }
   ],
   "source": [
    "gbn.rbmn <- bnfit2nbn(gaussian_total2)\n",
    "print8nbn(gbn.rbmn)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<span style=\"color:red\"><font size=\"6\"><b>Analyzing Faults</b></font></span>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<span style=\"color:purple\"><font size=\"5\"><b>[IDV1] Given</b></font></span> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Fault Occured at 162\n"
     ]
    },
    {
     "data": {
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      "text/plain": [
       "Plot with title \"Abnormal Likelihood Index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ALI(gaussian_total1, \"1\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 227,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in if (class(bn.fit) != \"bn.fit\") {:\n",
      "\"the condition has length > 1 and only the first element will be used\""
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      mu  s.d.\n",
      "F1 0.267 0.006\n",
      "             F1\n",
      "F1 3.635176e-05\n",
      "         mu  s.d.\n",
      "F2 3655.728 18.79\n",
      "         F2\n",
      "F2 353.0804\n",
      "         mu   s.d.\n",
      "F3 4442.624 25.027\n",
      "         F3\n",
      "F3 626.3647\n",
      "      mu  s.d.\n",
      "F4 9.239 0.053\n",
      "            F4\n",
      "F4 0.002837851\n",
      "       mu s.d.\n",
      "F5 36.768  0.2\n",
      "           F5\n",
      "F5 0.04019794\n",
      "       mu s.d.\n",
      "F6 47.378 0.21\n",
      "           F6\n",
      "F6 0.04416408\n",
      "         mu  s.d.\n",
      "P7 2831.673 0.983\n",
      "          P7\n",
      "P7 0.9661492\n",
      "       mu  s.d.\n",
      "L8 69.354 0.506\n",
      "         L8\n",
      "L8 0.256503\n",
      "        mu  s.d.\n",
      "T9 122.917 0.011\n",
      "             T9\n",
      "T9 0.0001190006\n",
      "       mu s.d.\n",
      "F10 0.049 0.01\n",
      "             F10\n",
      "F10 0.0001068873\n",
      "        mu s.d.\n",
      "T11 87.102 0.06\n",
      "            T11\n",
      "T11 0.003573657\n",
      "        mu  s.d.\n",
      "L12 43.726 1.025\n",
      "         L12\n",
      "L12 1.049669\n",
      "          mu  s.d.\n",
      "P13 2612.271 0.434\n",
      "          P13\n",
      "P13 0.1882575\n",
      "        mu  s.d.\n",
      "F14 26.144 0.131\n",
      "           F14\n",
      "F14 0.01714722\n",
      "        mu  s.d.\n",
      "L15 51.201 1.056\n",
      "        L15\n",
      "L15 1.11529\n",
      "          mu  s.d.\n",
      "P16 3257.622 0.486\n",
      "          P16\n",
      "P16 0.2361463\n",
      "        mu  s.d.\n",
      "F17 22.276 0.112\n",
      "           F17\n",
      "F17 0.01257527\n",
      "        mu  s.d.\n",
      "T18 67.423 0.046\n",
      "            T18\n",
      "T18 0.002156938\n",
      "        mu  s.d.\n",
      "F19 -0.454 1.127\n",
      "         F19\n",
      "F19 1.269551\n",
      "         mu  s.d.\n",
      "J20 246.072 0.323\n",
      "          J20\n",
      "J20 0.1043065\n",
      "         mu s.d.\n",
      "T21 102.995 0.02\n",
      "             T21\n",
      "T21 0.0003900809\n",
      "        mu  s.d.\n",
      "T22 87.153 0.149\n",
      "           T22\n",
      "T22 0.02227395\n",
      "      mu  s.d.\n",
      "R5 32.43 0.202\n",
      "           R5\n",
      "R5 0.04067995\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>F1</th><th scope=col>F2</th><th scope=col>F3</th><th scope=col>F4</th><th scope=col>F5</th><th scope=col>F6</th><th scope=col>P7</th><th scope=col>L8</th><th scope=col>T9</th><th scope=col>F10</th><th scope=col>...</th><th scope=col>F14</th><th scope=col>L15</th><th scope=col>P16</th><th scope=col>F17</th><th scope=col>T18</th><th scope=col>F19</th><th scope=col>J20</th><th scope=col>T21</th><th scope=col>T22</th><th scope=col>R5</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>0  </td><td>0  </td><td>0  </td><td>0  </td><td>0  </td><td>0  </td><td>0  </td><td>0  </td><td>0  </td><td>0  </td><td>...</td><td>0  </td><td>0  </td><td>0  </td><td>0  </td><td>0  </td><td>0  </td><td>0  </td><td>0  </td><td>0  </td><td>0  </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllllllllllllllllllllll}\n",
       " F1 & F2 & F3 & F4 & F5 & F6 & P7 & L8 & T9 & F10 & ... & F14 & L15 & P16 & F17 & T18 & F19 & J20 & T21 & T22 & R5\\\\\n",
       "\\hline\n",
       "\t 0   & 0   & 0   & 0   & 0   & 0   & 0   & 0   & 0   & 0   & ... & 0   & 0   & 0   & 0   & 0   & 0   & 0   & 0   & 0   & 0  \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "F1 | F2 | F3 | F4 | F5 | F6 | P7 | L8 | T9 | F10 | ... | F14 | L15 | P16 | F17 | T18 | F19 | J20 | T21 | T22 | R5 | \n",
       "|---|\n",
       "| 0   | 0   | 0   | 0   | 0   | 0   | 0   | 0   | 0   | 0   | ... | 0   | 0   | 0   | 0   | 0   | 0   | 0   | 0   | 0   | 0   | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  F1 F2 F3 F4 F5 F6 P7 L8 T9 F10 ... F14 L15 P16 F17 T18 F19 J20 T21 T22 R5\n",
       "1 0  0  0  0  0  0  0  0  0  0   ... 0   0   0   0   0   0   0   0   0   0 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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pQAwTZf3Pvs1Bv4F3gxByDY4u1B7y/j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\nIJQAgVACBEIJEAglQPB/NYoIdqdD2sUAAAAASUVORK5CYII=",
      "text/plain": [
       "Plot with title \"Bayesian Contribution index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bci_1a = BCI(gaussian_total1, \"default1\", 161, 160)\n",
    "bci_1a\n",
    "\n",
    "BCI_plot(bci_1a)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<span style=\"color:green\"><font size=\"5\"><b>[IDV1] Obtained</b></font></span> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 189,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Fault Occured at 162\n"
     ]
    },
    {
     "data": {
      "image/png": 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gkQCCVAIJQAgVACBEIJEAglQCCUAIFQ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\nnIu36ihSAAAAAElFTkSuQmCC",
      "text/plain": [
       "Plot with title \"Abnormal Likelihood Index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ALI(gaussian_total2, \"1\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 229,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in if (class(bn.fit) != \"bn.fit\") {:\n",
      "\"the condition has length > 1 and only the first element will be used\""
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>F1</th><th scope=col>F2</th><th scope=col>F3</th><th scope=col>F4</th><th scope=col>F5</th><th scope=col>F6</th><th scope=col>P7</th><th scope=col>L8</th><th scope=col>T9</th><th scope=col>F10</th><th scope=col>...</th><th scope=col>F14</th><th scope=col>L15</th><th scope=col>P16</th><th scope=col>F17</th><th scope=col>T18</th><th scope=col>F19</th><th scope=col>J20</th><th scope=col>T21</th><th scope=col>T22</th><th scope=col>R5</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>0.9551151</td><td>0.7131297</td><td>0.9345244</td><td>0.8628193</td><td>1.003125 </td><td>1.003125 </td><td>1.002822 </td><td>1.003125 </td><td>1.003125 </td><td>1.003125 </td><td>...      </td><td>0.9430289</td><td>0.8307169</td><td>1.003125 </td><td>0.8925847</td><td>1.003125 </td><td>1.003125 </td><td>1.003125 </td><td>1.003125 </td><td>1.003125 </td><td>1.003125 </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllllllllllllllllllllll}\n",
       " F1 & F2 & F3 & F4 & F5 & F6 & P7 & L8 & T9 & F10 & ... & F14 & L15 & P16 & F17 & T18 & F19 & J20 & T21 & T22 & R5\\\\\n",
       "\\hline\n",
       "\t 0.9551151 & 0.7131297 & 0.9345244 & 0.8628193 & 1.003125  & 1.003125  & 1.002822  & 1.003125  & 1.003125  & 1.003125  & ...       & 0.9430289 & 0.8307169 & 1.003125  & 0.8925847 & 1.003125  & 1.003125  & 1.003125  & 1.003125  & 1.003125  & 1.003125 \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "F1 | F2 | F3 | F4 | F5 | F6 | P7 | L8 | T9 | F10 | ... | F14 | L15 | P16 | F17 | T18 | F19 | J20 | T21 | T22 | R5 | \n",
       "|---|\n",
       "| 0.9551151 | 0.7131297 | 0.9345244 | 0.8628193 | 1.003125  | 1.003125  | 1.002822  | 1.003125  | 1.003125  | 1.003125  | ...       | 0.9430289 | 0.8307169 | 1.003125  | 0.8925847 | 1.003125  | 1.003125  | 1.003125  | 1.003125  | 1.003125  | 1.003125  | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  F1        F2        F3        F4        F5       F6       P7       L8      \n",
       "1 0.9551151 0.7131297 0.9345244 0.8628193 1.003125 1.003125 1.002822 1.003125\n",
       "  T9       F10      ... F14       L15       P16      F17       T18     \n",
       "1 1.003125 1.003125 ... 0.9430289 0.8307169 1.003125 0.8925847 1.003125\n",
       "  F19      J20      T21      T22      R5      \n",
       "1 1.003125 1.003125 1.003125 1.003125 1.003125"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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MrhW5R0YKatt7X0J5mcjgjl8C1KOjDT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\n",
      "text/plain": [
       "Plot with title \"Bayesian Contribution index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bci_1 = BCI(gaussian_total2, \"default1\", 161, 160)\n",
    "bci_1\n",
    "\n",
    "BCI_plot(bci_1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<span style=\"color:purple\"><font size=\"5\"><b>[IDV2] Given</b></font></span> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Fault Occured at 161\n"
     ]
    },
    {
     "data": {
      "image/png": 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VACBEIJEAglQCCUAIFQAgRCCRAIJUAg\nlACBUAIEQgkQCCVAIJQAgVACBEIJEAglQCCUAIFQAgRCCRAIJUAglACBUAIEQgkQCCVAIJQA\ngVACBEIJEPQZyv28lOnmfCff3otQAgPSYyj3VanNTncilMCz6DGUi7I61nJVTZs7EUrgWfQY\nyur0i7tqshNK4In0GMr3Nu6nU6EEnkiPoZyU/fulqVACz6PHUK7K/HxpV6ZCCTyNPk8PWlzq\nuClCCTyNXk84387eL+3mQgk8C+/MAQiEEiAQSoDgUaF0MAd4GsMJZbnWxhAA7fDSGyAQSoBA\nKAGCXkP5tpydPpJy8dbVEACt6/ODeydXR2umnQwB0IFeP7i3Wm+bS7tNVRZdDAHQgV4/uHd7\nubwtVRdDAHTgAR/c+/dCa0MAdMAWJUDQ7z7Kza65ZB8l8Ez6PD1oenXUe7L/7pZCCQxIv+dR\nLprzKKvZ0nmUwPPwzhyAQCgBAqEECIQSIBBKgEAoAQKhBAiEEiAQSoBAKAECoQQIhBIgEEqA\nQCgBAqEECIQSIBBKgEAoAQKhBAiEEiAQSoBAKAECoQQIhBIgEEqAQCgBAqEECIQSIBBKgEAo\nAQKhBAiEEiAQSoBAKAECoQQIhBIgEEqAQCgBAqEECIQSIBBKgEAoAQKhBAiEEiAQSoBAKAEC\noQQIhBIgEEqAQCgBAqEECIQSIBBKgEAoAQKhBAiEEiAQSoBAKAECoQQIhBIgEEqAQCgBAqEE\nCIQSIBBKgEAoAQKhBAh6DeXbclZqs8VbV0MAtK7HUO4n5cO0kyEAOtBjKBelWm+bS7tNVRZd\nDAHQgR5DWZXt5fK2VF0MAdCBHkNZylcLrQ0B0AFblABBv/soN7vmkn2UwDPp8/Sg6dVR78m+\nkyEA2tfveZSL5jzKarZ0HiXwPJ79nTnlSXX44AFte+5QPjp3v9HpAwi06dlD+byt7PQBBNr0\nqFC2ch7lJ538OpwPu+arH7TxMAJ9GE4ob1vy0zvpOXr/c41QwrN76pfeQgn04alDaR8l0Idn\nD+Xz6vQBBNr07B/c++Da/bf/fgyB/vngXoDAB/cCBD5mDSDwwb0AgS1KgMAH9wIEPrgXIPDB\nvQDBc78zB6AHQgkQCCVAIJQAgVACBAMNJcCA/EfF2g/jLwxrbbow/hm+wBTN8PUM6xEZ1tp0\nYfwzfIEpmuHrGdYjMqy16cL4Z/gCUzTD1zOsR2RYa9OF8c/wBaZohq9nWI/IsNamC+Of4QtM\n0Qxfz7AekWGtTRfGP8MXmKIZvp5hPSLDWpsujH+GLzBFM3w9w3pEhrU2XRj/DF9gimb4eob1\niAxrbbow/hm+wBTN8PUM6xEZ1tp0YfwzfIEpmuHrGdYjMqy16cL4Z/gCUzTD1zOsR2RYa9OF\n8c/wBaZohq/HIwIQCCVAIJQAgVACBEIJEAglQCCUAIFQAgRCCRAIJUAglACBUAIEQgkQCCVA\nIJQAgVACBAMK5aIq1WL/6LVo3WpymdbVDMc22bfzE2mkU9zOS5nvmovjnOH+82mNaIa/NJxQ\nTktt8ujVaNuimVZVP9muZji2ye6r0xNppFPcjP0PcVedZlj/WzDOGf7WYEL5VqrtYVuVt0ev\nSLu2ZX7867Uq85sZjm6ys9I8kcY6xeo4l/2sLEY7w3k9t+M/6iN/mv7CYEK5KJvj13VZPnpF\n2jU7PcB1R65mOLbJrssplCOd4rrJyL5Uo51heYmn6W8MJpSzUm/2b8vs0SvSifoZeDXDkU12\nV6anv2kjneK8bN8vjnSG5z0n9T8FI53hbw0mlFf/po3PvkxvZjiyyU7L7jSVkU5xUg7LqtmH\nMtYZLs8vvZejneFvDeYxGPUfyqp+DTPaZ+CyrA+jDmUps+ZQx2G0Mzys6qM51eow3hn+0mAe\ngzH/oeyq+sXLWJ+BzUuzkYeyPpgzH/P21rI5vl3vjBzrDH9pMI/BiP9Q9tW0/jbWZ+CkPm1m\n5KGs91Hu6vNkRjrDVf3S+/hPwWq0M/ytwTwG1Xj/UKanE9GuZjimyc6bQ6OnqYx0iuXTaY1p\nhpNS74Dd1/8UjHSGvzWYx+B0hG03viNsu8n09JaOqxmOabLlYrRTvDrHa6QzLKOf4W8NJpTL\nZsNk0xx9G5NNmZ4vXc1wTJO9DuVIp3iay67+kxzpDE/bjs2ZoiOd4W8NJpQjfRfA7tLJcb/l\nYdTvzNmVyb7eg7ce7QwXpX5H92LE7z36rcGE8jBptkqm+YZPZf6xuXU9w9FN9vzabaRTXH46\nrTHNcDr6Gf7ScEJ5+vySR69F265el17PcHSTPYdyrFPcTD+Z1qhm+Om0RjXD3xlOKAEGSigB\nAqEECIQSIBBKgEAoAQKhBAiEEiAQSoBAKAECoQQIhBIgEEqAQCgBAqEECIQSIBBKgEAoAQKh\nBAiEEiAQSoBAKAECoQQIhBIgEEqAQCgBAqEECIQSIBBKgEAoAQKhBAiEEiAQSoBAKHlaxbOX\nnniq8bSEkr54qvG0hJK+eKrxtISSvniqMRybaSnTTXNpVkq1qC8da7gs1fJwWJSyOC0vPq46\nWk1KtXrYKvMahJLBWJXGsXrL06VTGJuFuqHND87L08M5lLPyvgidEUoGoyrbw2FdJnUC1/Wl\n+tl5jOC+TmjztaqXq+1hW9U3qK/f1Ffsp2Xz6JVn1ISSwSh3uTuH8q35ujv/4HSjTZmdFmdl\nf1zc14vQGaFkMBalzLbb0+XdZjk9h/Jw8/V8BOf9Ynn3mFXmRXh+MRzL6li8qt52nF7qJ5QM\ngOcXQ7JZTOp9lPMyWW12Pwvl41aW1+FpxsBc8vdVKOt9lpsyf99H6TAO3RNKBmNyOtY9OdVw\n+9U+ytNR781pcV0vHlYO5tApoWQw1qe9jW/NYZ33i3+Hstl/OXv/4WlvZrNjE7oilAxH886c\n+pX1YV5fuJwDdLePclYmq48frialzHWSTgklz8XRGx7As47nIpQ8gGcdz0UoeQDPOp6LUPIA\nnnUAgVACBEIJEAglQCCUAIFQAgRCCRAIJUAglACBUAIEQgkQCCVAIJQAgVACBEIJEAglQCCU\nAIFQAgRCCRAIJUAglACBUAIEQgkQCCVAIJQAgVACBEIJEPwBKCOd80Fos4oAAAAASUVORK5C\nYII=",
      "text/plain": [
       "Plot with title \"Abnormal Likelihood Index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ALI(gaussian_total1, \"2\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in if (class(bn.fit) != \"bn.fit\") {:\n",
      "\"the condition has length > 1 and only the first element will be used\""
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>F1</th><th scope=col>F2</th><th scope=col>F3</th><th scope=col>F4</th><th scope=col>F5</th><th scope=col>F6</th><th scope=col>P7</th><th scope=col>L8</th><th scope=col>T9</th><th scope=col>F10</th><th scope=col>...</th><th scope=col>F14</th><th scope=col>L15</th><th scope=col>P16</th><th scope=col>F17</th><th scope=col>T18</th><th scope=col>F19</th><th scope=col>J20</th><th scope=col>T21</th><th scope=col>T22</th><th scope=col>R5</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>0.5979924</td><td>0.5484541</td><td>0.7338195</td><td>0.7087914</td><td>0.5239298</td><td>0.5816139</td><td>0.5050544</td><td>0.5301012</td><td>0.5118497</td><td>0.7264861</td><td>...      </td><td>0.5436004</td><td>0.4942924</td><td>0.1765009</td><td>0.5251283</td><td>0.7610984</td><td>0.7160505</td><td>0.5130444</td><td>0.6514402</td><td>0.6968609</td><td>0.5213831</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllllllllllllllllllllll}\n",
       " F1 & F2 & F3 & F4 & F5 & F6 & P7 & L8 & T9 & F10 & ... & F14 & L15 & P16 & F17 & T18 & F19 & J20 & T21 & T22 & R5\\\\\n",
       "\\hline\n",
       "\t 0.5979924 & 0.5484541 & 0.7338195 & 0.7087914 & 0.5239298 & 0.5816139 & 0.5050544 & 0.5301012 & 0.5118497 & 0.7264861 & ...       & 0.5436004 & 0.4942924 & 0.1765009 & 0.5251283 & 0.7610984 & 0.7160505 & 0.5130444 & 0.6514402 & 0.6968609 & 0.5213831\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "F1 | F2 | F3 | F4 | F5 | F6 | P7 | L8 | T9 | F10 | ... | F14 | L15 | P16 | F17 | T18 | F19 | J20 | T21 | T22 | R5 | \n",
       "|---|\n",
       "| 0.5979924 | 0.5484541 | 0.7338195 | 0.7087914 | 0.5239298 | 0.5816139 | 0.5050544 | 0.5301012 | 0.5118497 | 0.7264861 | ...       | 0.5436004 | 0.4942924 | 0.1765009 | 0.5251283 | 0.7610984 | 0.7160505 | 0.5130444 | 0.6514402 | 0.6968609 | 0.5213831 | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  F1        F2        F3        F4        F5        F6        P7       \n",
       "1 0.5979924 0.5484541 0.7338195 0.7087914 0.5239298 0.5816139 0.5050544\n",
       "  L8        T9        F10       ... F14       L15       P16       F17      \n",
       "1 0.5301012 0.5118497 0.7264861 ... 0.5436004 0.4942924 0.1765009 0.5251283\n",
       "  T18       F19       J20       T21       T22       R5       \n",
       "1 0.7610984 0.7160505 0.5130444 0.6514402 0.6968609 0.5213831"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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+vi9wc9rz++B4+jKImnKOcYjdG5NxavY+qvWat8Dh1IURJPUc4xGqNzbyxex+lF\nuc7fvsoLX2/Vb6XsQ1EST1HOMRqjc28sXsfk3x50dLEDRUk8RTnHaIzOvbF4HRQl8SnEh7K1\nWX3PvbF4HZN+wzkPvYk3Eh/K1mb1PffG4nXwYg7xKcSHsrVZfc+9sXgdE94e9P2xfi5a8mV3\nz7IPRUk8RTnHaIzOvbF4HbzhnPgU4kNpj36kJObeWLwOipL4FOJD2Ro98TPG66AoiU8iXuc+\nXCKT86vidVCUxBNPfELxOihK4oknPqF4HRQl8cQTn1C8DoqSeOKJTyheB0VJPPHEJxSvg6Ik\nnnjiE4rXQVESTzzxCcXroCiJJ574hOJ1UJTEE098QvE6KEriiSc+oXgdFCXxxBOfULwOipJ4\n4olPKF4HRUk88cQnFK+DoiSeeOITitdBURJPPPEJxeugKIknnviE4nVQlMQTT3xC8TooSuKJ\nJz6heB0UJfHEE59QvA6KknjiiU8oXgdFSTzxxCcUr4OiJJ544hOK10FREk888QnF66AoiSee\n+ITidVCUxBNPfELxOihK4oknPqF4HRQl8cQTn1C8DoqSeOKJTyheB0VJPPHEJxSvg6Iknnji\nE4rXQVESTzzxCcXroCiJJ574hOJ1UJTEE098QvE6KEriiSc+oXgdFCXxxBOfULwOipJ44olP\nKF4HRUk88cQnFK+DoiSeeOITitdBURJPPPEJxeugKIknnviE4nVQlMQTT3xC8TooSuKJJz6h\neB0UJfHEE59QvA6KknjiiU8oXgdFSTzxxCcUr4OiJJ544hOK10FREk888QnF66AoiSee+ITi\ndVCUxBNPfELxOihK4oknPqF4HRQl8cQTn1C8DoqSeOKJTyheB0VJPPHEJxSvg6IknnjiE4rX\nQVESTzzxCcXroCiJJ574hOJ1UJTEE098QvE6KEriiSc+oXgdFCXxxBOfULwOipJ44olPKF4H\nRUk88cQnFK+DoiSeeOITitdBURJPPPEJxeugKIknnviE4nVQlMQTT3xC8TooSuKJJz6heB0U\nJfHEE59QvA6KknjiiU8oXgdFSTzxxCcUr4OiJJ544hOK10FREk888QnF66AoiSee+ITidVCU\nxBNPfELxOihK4oknPqF4HROK8uvPOt96Xn98Dx5HURJPPPG/tSg/84PPoQMpSuKJJ/63FuU6\nf/sqL3y95a9DB1KUxBNP/G8tyjzvutiBoiSeeOIpSoqSeOKJNxKv4/SifM3feehNPPHE24rX\nwYs5xBNPfELxOia8Pej7Y/1ctOTL7p5lH4qSeOKJ/7VFORZFSTzxxFOUAoqSeOKJpyh51Zt4\n4ok3Eq9DqShb30FI0EiBxxNPPPG/JF5HhIfeAOAbRQkAAooSAAQRfs0aAPgW4QVIMYUAAApk\nSURBVCdzAMC3CL9mDQB8i/DbgwDAN4oSAAQRfs0aAPjGizkAIIjwa9YAwDfecA4AAooSAAQU\nJQAIKEoAEFCUACCgKAFAQFECgICiBAABRQkAAooSAAQUJQAIKEoAEFCUACCgKAFAQFECgICi\nBAABRQkAAooSAAQUJQAIrBZl/e+WVR++S/8gbvP4/97y/HX43ztrHv73JX/5CBvOqzCc5uHN\n642K/xDHszv47atxVeEK9cXP1/GTU1zr6zV/fv8eNfB6mYrbWHfdRt59/KZvgdvf1u6Y/uVt\nzkvjCn0L3DuYvuXtHE7v9PeMpnd9O4fTv7w9c9m7vt2HDy/v5mg/9S7s0XBaS9S5tD2HD27d\n/TWqEYzZVzPyUZTv4ow0jv+vujBYBo3D/5Z/Ck3ZHs5HQPF9jVnQZvybPJ768K/68rOQv7/0\nrzr836j4evjP/40YeL1M3/XghpI3zWXtWeDWZ3fHDCxvc14OV+hd4L7B9C5v13D617d7NP3r\n2zmc/uXtnsv+9e08XFjeTXs/9S9sezitJepe2u7Dh7fu4TqfI/fVjOwWZeODN3lGGge85e/F\n8ryMPPxlO+3/hKJpD+dLHE7j6/+K0Ugax3/lr9/bvT1m9O/1v6f+L/87Mr/4bjefw/HNa7wV\nW/qj93voXKby8Lf8j3SVw7L2LXDzs/tjBpa3PS/7K/QucM851r+8XcPpX9/u0fSvb/8p37u8\nP+eyf30744XlLa90mPDhhW2eNIclGti7Pw8f3rq747/LA0btqxl5KMrn58+QonzOjwOG4+Wj\nj77+8hxw+IfQYcfHv484fn94fbVnofgO+fmIyfl5E3Uj9wc3lmld3Of4ytfCVQ7L2rvAzVXd\nHzOwvK1Bt0O7H7x2DH5oebuG07++3aPpX9/+U753eX/OZf/6dsYLy1t+/TDhwwt7uInGEg3t\n3Z+HD2/d+vPFhVH7akYeivJ9xM7+ccDoe5QF8a+n5vF/8r8BRfmW/1vnL8K/fN44/jXvfRz0\n4/D9n+/DD6Wb+evqHkfvud59E+K5Xo5i/+HI0/2wrL0L3PwLpH3M0D3K6s/WFToXuPscG1je\nruH0r2/3aPrXt/eU71/en3PZv76d8dLfm42/YV/kuyDtr5RLNLR3Ow4/utR5/PfuzueIfTUj\nu0XZeg5iRFG2n7P4N+5ZvuqjtVgcjeOLv1HloqwPX1eXhtuvcfz2f9sTYLj4qpv/fsvfyg+/\nxUfSrXusW/Kjlv01Xot57H+KuHOZhndfq+7yrs92H9v6qHt5j+blcIXuBe4c/NDydg2nf327\nR9O/vn2n/MDydsxl7/p2xgvLe7iBcsLH1+qmsUTjivKwor1bt/Uc5ah9NaNEi/K/595HEx2H\nv79ITdk4/vn5O6QoyyfWP/abZczxr7tTQT58d5r8ER+FNMZbnmDiHcr6Gp/F4a/WirJneY/m\npXGHq3OBOwc/tLxdw+lf3+7R9K9v3yk/sLwdc9m7vp3xwvLWN1BNeEhRHpZoVFEeDu/fuvvv\nYPdujxH7akZ2i3LoQ+l4qSd/5P0V7mQdjn8rFkguSukTvV8u7w589D9rVB1TeN6/8eRZmpzW\nw7jhZ+9/XOPftmO+Rz56ilWUfct7NC/Nq3ctcNfgB5e39w5u5zW6R9O/vn2n/MDy/hxC//p2\nxw8v7/6o3YQHFGVjicacPGN6sjr+X2vqxF6YTZJF+SX15IQmy4/+Zp45/oSXor6GW7V9hd25\nLrzIf3QT/416MWfT3kl9tzG9KHuX9zhEqLKuwQ8ub2hRdn3cv749p/zQ8v4cQv/c9++o/uXd\nHbWfcOnkOWQ2l2hEUR4OH9q6+78KXo8/FUOKRfl3/GsVm+LM/ZZv4PSi3G2M4WcRG8evg4vy\nQ3oTaEdRBtwH3RQP0Ea9PWj/4cu4V707xjUcv/uof3n7qqlngWcpyv717R5N//r2nPJDy9tb\nlOPjN33L+5rvj6onfHhhG5mtJZKL8nD44NbdHf9Svj9p1L6aUYJF+Snfw2oe/l7Mu/wkYtBw\nGl/fvVNN+lGb+uLf6qHZ4HDaN7/ufgdw9xXWxRNewiP75jVetg9Fv/tvoXNe3ovRv/U/Jd91\neXwzDSxvdzX1LnDvovYtb9dw+te3ezT969sznKHl/TmX/evb83da7/K+bJPKoMOEDy/s4SY+\nxz08/nn48NbdHf9VvuV91L6aUYJF+Rp2l+/7uXwqSXpZOmg4zcc1Zfzo9znuhz84nPbNv+T9\nP4JWX2E/JbsfaBhdrR/l4YNvSP7x4e42ekYVVpTNpaz+HFje7mrqXeATivLncPrXt3s0/evb\nM5yh5f05l/3r2xk/sLzVlz6aEz68sIebeO2Yp1GHD2/d/ef/FNM9al/NKMGiDH0Ssfj50jfh\nbQanF+Xmv/X2TBSqrJX3/py/DhdZ5yPS4SvUU/K1Hc5afvtZHTr8k+fd8zL48+RTi3JgeXuq\nqW+BZynK/vXtGU3v+vYMZ2h5O+ayd3274weW9+O5+lLjuxZ+UcBhyEFFeTh8eOvWny8ffI/Z\nVzOyWpQAYAZFCQACihIABBQlAAgoSgAQUJQAIKAoAUBAUQKAgKIEAAFFCQACihIABBQlAAgo\nSgAQUJQAIKAoAUBAUQKAgKIEAAFFCQACihIABBQlAAgoSgAQUJQAIKAoAUBAUQKAgKIEAAFF\nCQACihIABBQlAAgoSgAQUJQAIKAoAUBAUQKAgKIEAAFFiWXdZ2f15bPs7ucBWdb3YcbZi0g4\n1bCwVXa/u/SYrTq+TlFieZxqWNh1drW7dFVfGkBRYgGcaljYU30/cpU9yodTlFgApxqWdr57\nZvI+O9/+/+4iy1blPcssezrLLqo6bH52e8+zvrh1c5atbsqAu/MsO+94lhOYiqLE0u6yy/LP\ny6Iwr7NSUYRZdlFcKOrw+LNZ2allUZYflR/eVAfdLPedIFkUJRa3qs7Csvey7Hazud1dPH/a\nfbr12dXD5mFVfKL4+K446Km8U7rKHoqDzgZuCTgNRYnFXRWtt624w0s5u0q8ry83P1s8uL7b\nPiYvP77IijJ9qj7kYTeUUJRY3EP5yPm8uEO49Xh3fb6rxPLj6o+uz1b/7RR9m108PCzxDSB5\nFCWWd7a9W/i0e8x8vu+9VlF2fvaoKDfXq+2fqxGvnAOBKEos7ya73lxXr8JcZmc3d4/Hldj9\n2f1/B3dXZzxHCQUUJZZX3Js8K59srIqvsxLrzxbPXDaeozx6YpI3V0IBZxUMuMz27xEqevCh\n49nIxmerV73vqq/cFh9u75JeFA/gb3nVGzooShhwl+1fsr7aPeV43yrK1mcvi0sXm9azl8Uz\nk7f1McDMKEpYsKp/jnFbg+f39SPrze6P1mevstV1/ZXiJ3Oyy/IVnPInc+hJKKAoAUBAUQKA\ngKIEAAFFCQACihIABBQlAAgoSgAQUJQAIKAoAUBAUQKAgKIEAAFFCQACihIABBQlAAgoSgAQ\nUJQAIKAoAUBAUQKAgKIEAAFFCQACihIABBQlAAgoSgAQUJQAIKAoAUBAUQKAgKIEAAFFCQAC\nihIABBQlAAgoSgAQ/B88X72d024fxQAAAABJRU5ErkJggg==",
      "text/plain": [
       "Plot with title \"Bayesian Contribution index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bci_2a = BCI(gaussian_total1, \"default2\", 161, 160)\n",
    "bci_2a\n",
    "\n",
    "BCI_plot(bci_2a)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<span style=\"color:green\"><font size=\"5\"><b>[IDV2] Obtained</b></font></span> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Fault Occured at 161\n"
     ]
    },
    {
     "data": {
      "image/png": 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VACBEIJEAglQCCUAIFQAgRCCRAIJUAg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\nYII=",
      "text/plain": [
       "Plot with title \"Abnormal Likelihood Index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ALI(gaussian_total2, \"2\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in if (class(bn.fit) != \"bn.fit\") {:\n",
      "\"the condition has length > 1 and only the first element will be used\""
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>F1</th><th scope=col>F2</th><th scope=col>F3</th><th scope=col>F4</th><th scope=col>F5</th><th scope=col>F6</th><th scope=col>P7</th><th scope=col>L8</th><th scope=col>T9</th><th scope=col>F10</th><th scope=col>...</th><th scope=col>F14</th><th scope=col>L15</th><th scope=col>P16</th><th scope=col>F17</th><th scope=col>T18</th><th scope=col>F19</th><th scope=col>J20</th><th scope=col>T21</th><th scope=col>T22</th><th scope=col>R5</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>0.5977001</td><td>0.548454 </td><td>0.7338017</td><td>0.7087914</td><td>0.5275522</td><td>0.5816139</td><td>0.4806947</td><td>0.5335015</td><td>0.5136822</td><td>0.7264861</td><td>...      </td><td>0.5437567</td><td>0.4954186</td><td>0.1842437</td><td>0.5229143</td><td>0.8576306</td><td>0.7219253</td><td>0.5073128</td><td>0.6286364</td><td>0.7645311</td><td>0.5213561</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllllllllllllllllllllll}\n",
       " F1 & F2 & F3 & F4 & F5 & F6 & P7 & L8 & T9 & F10 & ... & F14 & L15 & P16 & F17 & T18 & F19 & J20 & T21 & T22 & R5\\\\\n",
       "\\hline\n",
       "\t 0.5977001 & 0.548454  & 0.7338017 & 0.7087914 & 0.5275522 & 0.5816139 & 0.4806947 & 0.5335015 & 0.5136822 & 0.7264861 & ...       & 0.5437567 & 0.4954186 & 0.1842437 & 0.5229143 & 0.8576306 & 0.7219253 & 0.5073128 & 0.6286364 & 0.7645311 & 0.5213561\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "F1 | F2 | F3 | F4 | F5 | F6 | P7 | L8 | T9 | F10 | ... | F14 | L15 | P16 | F17 | T18 | F19 | J20 | T21 | T22 | R5 | \n",
       "|---|\n",
       "| 0.5977001 | 0.548454  | 0.7338017 | 0.7087914 | 0.5275522 | 0.5816139 | 0.4806947 | 0.5335015 | 0.5136822 | 0.7264861 | ...       | 0.5437567 | 0.4954186 | 0.1842437 | 0.5229143 | 0.8576306 | 0.7219253 | 0.5073128 | 0.6286364 | 0.7645311 | 0.5213561 | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  F1        F2       F3        F4        F5        F6        P7       \n",
       "1 0.5977001 0.548454 0.7338017 0.7087914 0.5275522 0.5816139 0.4806947\n",
       "  L8        T9        F10       ... F14       L15       P16       F17      \n",
       "1 0.5335015 0.5136822 0.7264861 ... 0.5437567 0.4954186 0.1842437 0.5229143\n",
       "  T18       F19       J20       T21       T22       R5       \n",
       "1 0.8576306 0.7219253 0.5073128 0.6286364 0.7645311 0.5213561"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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bwf5xfld5rZZBcpSuIXjnela7Panntl8X6cX5Sb9HO//7fOmpKiJH7heFe6Nqvt\nuVcW78f5RVm0439ZU1KUxC8c70rXZrU998ri/ZhalIem3FKUxC8d70rXZrU998ri/Ti/KD+y\nh94Hu3RDURK/cLwrXZvV9twri/fj/KL8Ly378W9KURK/cLwrXZvV9twri/djwtuD/vtYFxe+\nNxQl8cvGu9K1WW3PvbJ4P3jDOfExxLvStVltz72yeD8oSuJjiHela7Panntl8X7MUpQ8R0n8\nwvGudG1W23OvLN4PT0XZ+hs4BOmacuLNxLvStVltz72yeD946E18DPGudG1W23OvLN4PipL4\nKOLHCjN6R8bnXle8HxQl8cTPHu9I2ehtx/sxoSh3f7bZP9Hr7dfP4HEUJfGXFu9I2ehtx/sx\n9WPWCt9DB1KUxF9avCNlo7cd78f5RblNP3b5hd1H8amUfShK4i8t3pGy0duO92PypwedXOxA\nURJ/afGOlI3edrwfFCXxxM8f7+U1+Fgmx2+8H5M+4ZyH3sQTT7yueD94MYd44omPKN6PCW8P\n+vnarrOWfC/vWfahKIknnviLLcqxKEriiSeeohRQlMQTTzxFKaAoiSeeeIpSQFESTzzxFKWA\noiSeeOIpSgFFSTzxxFOUAoqSeOKJpygFFCXxxBNPUQooSuKJJ56iFFCUxBNPPEUpoCiJJ554\nilJAURJPPPEUpYCiJJ544ilKAUVJPPHEU5QCipJ44omnKAUUJfHEE09RCihK4oknnqIUUJTE\nE088RSmgKIknnniKUkBREk888RSlgKIknnjiKUoBRUk88cRTlAKKknjiiacoBRQl8cQTT1EK\nKEriiSeeohRQlMQTTzxFKaAoiSeeeIpSQFESTzzxFKWAoiSeeOIpSgFFSTzxxFOUAoqSeOKJ\npygFFCXxxBNPUQooSuKJJ56iFFCUxBNPPEUpoCiJJ554ilJAURJPPPEUpYCiJJ544ilKAUVJ\nPPHEU5QCipJ44omnKAUUJfHEE09RCihK4oknnqIUUJTEE088RSmgKIknnniKUkBREk888RSl\ngKIknnjiKUoBRUk88cRTlAKKknjiiacoBRQl8cQTT1EKKEriiSeeohRQlMQTTzxFKaAoiSee\neIpSQFESTzzxFKWAoiSeeOIpSgFFSTzxxFOUAoqSeOKJpygFFCXxxBNPUQooSuKJJ56iFFCU\nxBNPPEUpoCiJJ554ilJAURJPPPEUpYCiJJ544ilKAUVJPPHEU5QCipJ44omnKAUUJfHEE09R\nCihK4oknnqIUUJTEE088RSmgKIknnniKUkBREk888RSlgKIknnjiKUoBRUk88cRTlAKKknji\niacoBRQl8cQTT1EKKEriiSeeohRQlMQTTzxFKaAoiSeeeIpSQFESTzzxFKWAopIcJYYAAAse\nSURBVCSeeOIvtih3f7bpwXr79TN4HEVJPPHEX2pRfqe176EDKUriiSf+Uotym37s8gu7j3Qz\ndCBFSTzxxF9qUaZp18UOFCXxxBNPUVKUxBNPvJJ4P84vyk36yUNv4oknXle8H7yYQzzxxEcU\n78eEtwf9fG3XWUu+l/cs+1CUxBNP/MUW5VgUJfHEE09RCihK4oknnqLkVW/iiSdeSbwfnoqy\n9TdwCRrJ8XjiiSf+QuL9CPDQGwBsoygBQEBRAoAgwMesAYBtAX4zBwBsC/AxawBgW4BPDwIA\n2yhKABAE+Jg1ALCNF3MAQBDgY9YAwDbecA4AAooSAAQUJQAIKEoAEFCUACCgKAFAQFECgICi\nBAABRQkAAooSAAQUJQAIKEoAEFCUACCgKAFAQFECgICiBAABRQkAAooSAAQUJQAItBZl9d8t\nK778lP6DuM3j//tI083wf++sefjf9/T9y204G2E4zcOb1xsV/yWOpzz4Y9e4qnCF6uL3Zvzk\nZNfabdL158+ogVfLlN3Gtus20u7j930L3P5rlcf0L29zXhpX6Fvg3sH0LW/ncHqnv2c0vevb\nOZz+5e2Zy9717T58eHn3J/upd2FPhtNaos6l7Tl8cOser1GMYMy+mpGNovwUZ6Rx/H/FhcEy\naBz+N/9TaMr2cL4cim83ZkGb8R/yeKrDd9XltZB/vPSvOPzfqPhq+Ov/Rgy8WqafanBDyfvm\nsvYscOu75TEDy9ucl/oKvQvcN5je5e0aTv/6do+mf307h9O/vN1z2b++nYcLy7tv76f+hW0P\np7VE3Uvbffjw1q2v8z1yX81Ib1E2vviQZ6RxwEf6mS3P+8jD3w/T/k8omvZwduJwGj//l41G\n0jh+l25+Dnt7zOg/q/+e+r/078j87G+7/x6Ob17jI9vSX71/h85lyg//SP9IV6mXtW+Bm989\nHjOwvO15OV6hd4F7zrH+5e0aTv/6do+mf337T/ne5f09l/3r2xkvLG9+pXrChxe2edLUSzSw\nd38fPrx1y+N/8gNG7asZWSjK9frbpSjX6WnAcLx89MnP39cOh38JHXZ6/OeI44+HV1dbC8VX\n56cjJuf3TVSN3B/cWKZtdp9jl26Fq9TL2rvAzVU9HjOwvK1Bt0O7H7x2DH5oebuG07++3aPp\nX9/+U753eX/PZf/6dsYLy5v/vJ7w4YWtb6KxREN79/fhw1u3+n52YdS+mpGFovwcsbN/HTD6\nHmVG/Oepefyf9K9DUX6k/7bpu/BfPm8cv0l7Hwf9Ovz45+fwQ+lm/ra4x9F7rnffhHiu56M4\nfjnydK+XtXeBm/+AtI8ZukdZ/Nm6QucCd59jA8vbNZz+9e0eTf/69p7y/cv7ey7717czXvp3\ns/Ev7Lt8F6T9k3yJhvZux+EnlzqP/ynvfI7YVzPSW5St5yBGFGX7OYt/457lK77aisXROD77\nF1UuyurwbXFpuP0axx/+73ACDBdfcfM/H+lH/uWP+Ei6dY/1QH7UcrzGJpvH/qeIO5dpePe1\n6i7t+m73sa2vupf3ZF7qK3QvcOfgh5a3azj969s9mv717TvlB5a3Yy5717czXlje+gbyCR9f\nq/vGEo0rynpFe7du6znKUftqRpEW5X/r3kcTHYd/vktN2Th+vf5xKcr8ifWv42YZc/ymPBXk\nw8vT5I/4KKQx3vwEE+9QVtf4zg7faCvKnuU9mZfGHa7OBe4c/NDydg2nf327R9O/vn2n/MDy\ndsxl7/p2xgvLW91AMeEuRVkv0aiirA/v37rHv0H5bo8R+2pGeoty6EvpeKknf+X9Fe5k1cd/\nZAskF6X0jd4f53cHvvqfNSqOyayPbzxZS5PTehg3/Oz9r2v8O3TMz8hHT6GKsm95T+alefWu\nBe4a/ODy9t7B7bxG92j617fvlB9Y3t9D6F/f7vjh5T0eVU64Q1E2lmjMyTOmJ4vj/7WmTuyF\n2URZlDupJyc0WXryL/PM8We8FLUbbtX2FcpzXXiR/+Qm/hv1Ys6+vZP6bmN6UfYu72mIUGVd\ngx9cXtei7Pq6f317Tvmh5f09hP65799R/ctbHnWccOnkqTObSzSiKOvDh7bu8Z+Czem3Qoix\nKP+Of61in525P/INnF+U5cYYfhaxcfzWuSi/pDeBdhSlw33QffYAbdTbg45fvo971btjXMPx\n5Vf9y9tXTT0LPEtR9q9v92j617fnlB9a3t6iHB+/71veTXo8qprw4YVtZLaWSC7K+vDBrVse\n/56/P2nUvppRhEX5Ld/Dah7+mc27/CSi03AaPy/fqSb9qk118W/x0GxwOO2b33a/A7j7Ctvs\nCS/hkX3zGu+Hh6I//bfQOS+f2eg/+p+S77o8vpkGlre7mnoXuHdR+5a3azj969s9mv717RnO\n0PL+nsv+9e35N613ed8PSXlQPeHDC1vfxPe4h8e/Dx/euuXxu/wt76P21YwiLMqN212+n3X+\nVJL0srTTcJqPa/L40e9zPA5/cDjtm39P+38FrbrCcUrKX2gYXa1f+eGDb0j+9WV5Gz2jcivK\n5lIWfw4sb3c19S7wGUX5ezj969s9mv717RnO0PL+nsv+9e2MH1je4kdfzQkfXtj6JjYd8zTq\n8OGte/z+n2y6R+2rGUVYlK5PIma/X/ohvM3g/KLc/7c9nIlClbXyPtfpZrjIOh+RDl+hmpLd\nYThb+e1nVejwb553z8vg75NPLcqB5e2ppr4FnqUo+9e3ZzS969sznKHl7ZjL3vXtjh9Y3q91\n8aPG31r4oIB6yE5FWR8+vHWr7+cPvsfsqxlpLUoAUIOiBAABRQkAAooSAAQUJQAIKEoAEFCU\nACCgKAFAQFECgICiBAABRQkAAooSAAQUJQAIKEoAEFCUACCgKAFAQFECgICiBAABRQkAAooS\nAAQUJQAIKEoAEFCUACCgKAFAQFECgICiBAABRQkAAooSAAQUJQAIKEoAEFCUACCgKAFAQFEC\ngICixLKek6vq8lXy9PuAJOn7MuHsRSCcaljYKnkuL70mq46fU5RYHqcaFnaf3JWX7qpLAyhK\nLIBTDQt7q+5HrpJX+XCKEgvgVMPSrstnJp+T68P/P90kySq/Z5kkb1fJTVGHze8e7nlWFw8e\nrpLVQx7wdJ0k1x3PcgJTUZRY2lNym/95mxXmfZLLijBJbrILWR2efjfJOzUvyvyr/MuH4qCH\n5f4miBZFicWtirMw770kedzvH8uL12/lt1vfXb3sX1bZN7Kvn7KD3vI7pavkJTvoauCWgPNQ\nlFjcXdZ6h4qrX8opK/G5utz8bvbg+unwmDz/+ibJyvSt+JKH3fCEosTiXvJHztfZHcKD16f7\n67IS86+LP7q+W/yvlPVtcvPyssRfANGjKLG8q8PdwrfyMfP1sfdaRdn53ZOi3N+vDn+uRrxy\nDjiiKLG8h+R+f1+8CnObXD08vZ5WYvd3j/+rPd1d8RwlPKAosbzs3uRV/mRjUXydlVh9N3vm\nsvEc5ckTk7y5Eh5wVkGB2+T4HqGsB186no1sfLd41fup+Mlj9uXhLulN9gD+kVe94QdFCQWe\nkuNL1nflU47PraJsffc2u3Szbz17mT0z+VgdA8yMooQGq+r3GA81eP1cPbLel3+0vnuXrO6r\nn2S/mZPc5q/g5L+ZQ0/CA4oSAAQUJQAIKEoAEFCUACCgKAFAQFECgICiBAABRQkAAooSAAQU\nJQAIKEoAEFCUACCgKAFAQFECgICiBAABRQkAAooSAAQUJQAIKEoAEFCUACCgKAFAQFECgICi\nBAABRQkAAooSAAQUJQAIKEoAEFCUACCgKAFAQFECgICiBADB/wF281moG4/yuAAAAABJRU5E\nrkJggg==",
      "text/plain": [
       "Plot with title \"Bayesian Contribution index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bci_2 = BCI(gaussian_total2, \"default2\", 161, 160)\n",
    "bci_2\n",
    "\n",
    "BCI_plot(bci_2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<span style=\"color:purple\"><font size=\"5\"><b>[IDV3] Given</b></font></span> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Fault Occured at 161\n"
     ]
    },
    {
     "data": {
      "image/png": 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qEECIQSIBBKgEAoAQKhBAiEEiAQSoBA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\nQmCC",
      "text/plain": [
       "Plot with title \"Abnormal Likelihood Index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ALI(gaussian_total1, \"3\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in if (class(bn.fit) != \"bn.fit\") {:\n",
      "\"the condition has length > 1 and only the first element will be used\""
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>F1</th><th scope=col>F2</th><th scope=col>F3</th><th scope=col>F4</th><th scope=col>F5</th><th scope=col>F6</th><th scope=col>P7</th><th scope=col>L8</th><th scope=col>T9</th><th scope=col>F10</th><th scope=col>...</th><th scope=col>F14</th><th scope=col>L15</th><th scope=col>P16</th><th scope=col>F17</th><th scope=col>T18</th><th scope=col>F19</th><th scope=col>J20</th><th scope=col>T21</th><th scope=col>T22</th><th scope=col>R5</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>0.495094 </td><td>0.4940361</td><td>0.4924913</td><td>0.4975459</td><td>0.4932333</td><td>0.5202141</td><td>0.5512181</td><td>0.4873194</td><td>0.5005331</td><td>0.5213549</td><td>...      </td><td>0.4831153</td><td>0.5061478</td><td>0.1699648</td><td>0.5135149</td><td>0.5023036</td><td>0.4950345</td><td>0.6067311</td><td>0.5274916</td><td>0.494311 </td><td>0.4889751</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllllllllllllllllllllll}\n",
       " F1 & F2 & F3 & F4 & F5 & F6 & P7 & L8 & T9 & F10 & ... & F14 & L15 & P16 & F17 & T18 & F19 & J20 & T21 & T22 & R5\\\\\n",
       "\\hline\n",
       "\t 0.495094  & 0.4940361 & 0.4924913 & 0.4975459 & 0.4932333 & 0.5202141 & 0.5512181 & 0.4873194 & 0.5005331 & 0.5213549 & ...       & 0.4831153 & 0.5061478 & 0.1699648 & 0.5135149 & 0.5023036 & 0.4950345 & 0.6067311 & 0.5274916 & 0.494311  & 0.4889751\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "F1 | F2 | F3 | F4 | F5 | F6 | P7 | L8 | T9 | F10 | ... | F14 | L15 | P16 | F17 | T18 | F19 | J20 | T21 | T22 | R5 | \n",
       "|---|\n",
       "| 0.495094  | 0.4940361 | 0.4924913 | 0.4975459 | 0.4932333 | 0.5202141 | 0.5512181 | 0.4873194 | 0.5005331 | 0.5213549 | ...       | 0.4831153 | 0.5061478 | 0.1699648 | 0.5135149 | 0.5023036 | 0.4950345 | 0.6067311 | 0.5274916 | 0.494311  | 0.4889751 | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  F1       F2        F3        F4        F5        F6        P7       \n",
       "1 0.495094 0.4940361 0.4924913 0.4975459 0.4932333 0.5202141 0.5512181\n",
       "  L8        T9        F10       ... F14       L15       P16       F17      \n",
       "1 0.4873194 0.5005331 0.5213549 ... 0.4831153 0.5061478 0.1699648 0.5135149\n",
       "  T18       F19       J20       T21       T22      R5       \n",
       "1 0.5023036 0.4950345 0.6067311 0.5274916 0.494311 0.4889751"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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hxQ9+PxU/2cW+G5r3xpY42+jHVR/tp+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\nRU5ErkJggg==",
      "text/plain": [
       "Plot with title \"Bayesian Contribution index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bci_3a = BCI(gaussian_total1, \"default3\", 161, 160)\n",
    "bci_3a\n",
    "\n",
    "BCI_plot(bci_3a)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<span style=\"color:green\"><font size=\"5\"><b>[IDV3] Obtained</b></font></span> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Fault Occured at 161\n"
     ]
    },
    {
     "data": {
      "image/png": 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qEECIQSIBBKgEAoAQKhBAiEEiAQSoBA\nKAECoQQIhBIgEEqAQCgBAqEECIQSIBBKgEAoAQKhBAiEEiAQSoBAKAECoQQIhBIgEEqAQCgB\nAqEECIQSIOgylPt5KdPN+U5+vBehBHqkw1Duq1Kbne5EKIGh6DCUi7I61nJVTZs7EUpgKDoM\nZXX6xV012QklMCAdhvK9jfvpVCiBAekwlJOyf780FUpgODoM5arMz5d2ZSqUwGB0eXrQ4lLH\nTRFKYDA6PeF8O3u/tJsLJTAU3pkDEAglQCCUAMGzQulgDjAY/QllufaIIQAew0tvgEAoAQKh\nBAg6DeXbcnb6SMrFW1tDADxclx/cO7k6WjNtZQiAFnT6wb3Vettc2m2qsmhjCIAWdPrBvdvL\n5W2p2hgCoAVP+ODezwsPGwKgBbYoAYJu91Fuds0l+yiBIeny9KDp1VHvyf6nWwol0CPdnke5\naM6jrGZL51ECw+GdOQCBUAIEQgkQCCVAIJQAgVACBEIJEAglQCCUAIFQAgRCCRAIJUAglACB\nUAIEQgkQCCVAIJQAgVACBEIJEAglQCCUAIFQAgRCCRAIJUAglACBUAIEQgkQCCVAIJQAgVAC\nBEIJEAglQCCUAIFQAgRCCRAIJUAglACBUAIEQgkQCCVAIJQAgVACBEIJEAglQCCUAIFQAgRC\nCRAIJUAglACBUAIEQgkQCCVAIJQAgVACBEIJEAglQCCUAIFQAgRCCRAIJUAglACBUAIEQgkQ\nCCVAIJQAgVACBEIJEHQayrflrNRmi7e2hgB4uA5DuZ+UD9NWhgBoQYehXJRqvW0u7TZVWbQx\nBEALOgxlVbaXy9tStTEEQAs6DGUp3y08bAiAFtiiBAi63Ue52TWX7KMEhqTL04OmV0e9J/tW\nhgB4vG7Po1w051FWs6XzKIHhGPo7c8pAtfjgAY827FA+O3d/0eoDCDzS0EPZu1b+eoVafQCB\nR3pWKB9yHuUXWfq+U0+75rsfPOJhBLrQn1DetuS3d9Jx9P7lGqGEoRv0S2+hBLow6FDaRwl0\nYeihHK5WH0DgkYb+wb1Prt0/++fHEOieD+4FCHxwL0DgY9YAAh/cCxDYogQIfHAvQOCDewEC\nH9wLEAz7nTkAHRBKgEAoAQKhBAiEEiDoaSgBeuQfKvb4MP5Bv9amDeOf4QtM0QxfT78ekX6t\nTRvGP8MXmKIZvp5+PSL9Wps2jH+GLzBFM3w9/XpE+rU2bRj/DF9gimb4evr1iPRrbdow/hm+\nwBTN8PX06xHp19q0YfwzfIEpmuHr6dcj0q+1acP4Z/gCUzTD19OvR6Rfa9OG8c/wBaZohq+n\nX49Iv9amDeOf4QtM0QxfT78ekX6tTRvGP8MXmKIZvp5+PSL9Wps2jH+GLzBFM3w9/XpE+rU2\nbRj/DF9gimb4ejwiAIFQAgRCCRAIJUAglACBUAIEQgkQCCVAIJQAgVACBEIJEAglQCCUAIFQ\nAgRCCRAIJUDQo1AuqlIt9s9ei4dbTS7Tuprh2Cb7dn4ijXSK23kp811zcZwz3H89rRHN8I/6\nE8ppqU2evRqPtmimVdVPtqsZjm2y++r0RBrpFDdj/0PcVacZ1v8WjHOGf9WbUL6VanvYVuXt\n2SvyWNsyP/71WpX5zQxHN9lZaZ5IY51idZzLflYWo53hvJ7b8R/1kT9N/6A3oVyUzfHruiyf\nvSKPNTs9wHVHrmY4tsmuyymUI53iusnIvlSjnWF5iafpX/QmlLNSb/Zvy+zZK9KK+hl4NcOR\nTXZXpqe/aSOd4rxs3y+OdIbnPSf1PwUjneFf9SaUV/+mjc++TG9mOLLJTsvuNJWRTnFSDsuq\n2Ycy1hkuzy+9l6Od4V/15jEY9R/Kqn4NM9pn4LKsD6MOZSmz5lDHYbQzPKzqoznV6jDeGf5R\nbx6DMf+h7Kr6xctYn4HNS7ORh7I+mDMf8/bWsjm+Xe+MHOsM/6g3j8GI/1D21bT+NtZn4KQ+\nbWbkoaz3Ue7q82RGOsNV/dL7+E/BarQz/KvePAbVeP9QpqcT0a5mOKbJzptDo6epjHSK5ctp\njWmGk1LvgN3X/xSMdIZ/1ZvH4HSEbTe+I2y7yfT0lo6rGY5psuVitFO8OsdrpDMso5/hX/Um\nlMtmw2TTHH0bk02Zni9dzXBMk70O5UineJrLrv6THOkMT9uOzZmiI53hX/UmlCN9F8Du0slx\nv+Vh1O/M2ZXJvt6Dtx7tDBelfkf3YsTvPfqr3oTyMGm2Sqb5hoMy/9jcup7h6CZ7fu020iku\nv5zWmGY4Hf0M/6g/oTx9fsmz1+LRrl6XXs9wdJM9h3KsU9xMv5jWqGb45bRGNcO/6U8oAXpK\nKAECoQQIhBIgEEqAQCgBAqEECIQSIBBKgEAoAQKhBAiEEiAQSoBAKAECoQQIhBIgEEqAQCgB\nAqEECIQSIBBKgEAoAQKhBAiEEiAQSoBAKAECoQQIhBIgEEqAQCgBAqEECIQSIBBKgEAoGazi\n2UtHPNUYLKGkK55qDJZQ0hVPNQZLKOmKpxr9sZmWMt00l2alVIv60rGGy1ItD4dFKYvT8uLj\nqqPVpFSrp60yr0Eo6Y1VaRyrtzxdOoWxWagb2vzgvDw9nEM5K++L0BqhpDeqsj0c1mVSJ3Bd\nX6qfnccI7uuENl+rernaHrZVfYP6+k19xX5aNs9eeUZNKOmNcpe7cyjfmq+78w9ON9qU2Wlx\nVvbHxX29CK0RSnpjUcpsuz1d3m2W03MoDzdfz0dw3i+Wd89ZZV6E5xf9sayOxavqbcfppX5C\nSQ94ftEnm8Wk3kc5L5PVZve7UD5vZXkdnmb0zCV/34Wy3me5KfP3fZQO49A+oaQ3Jqdj3ZNT\nDbff7aM8HfXenBbX9eJh5WAOrRJKemN92tv41hzWeb/4OZTN/svZ+w9PezObHZvQFqGkP5p3\n5tSvrA/z+sLlHKC7fZSzMll9/HA1KWWuk7RKKBkWR294As86hkUoeQLPOoZFKHkCzzqGRSh5\nAs86gEAoAQKhBAiEEiAQSoBAKAECoQQIhBIgEEqAQCgBAqEECIQSIBBKgEAoAQKhBAiEEiAQ\nSoBAKAECoQQIhBIgEEqAQCgBAqEECIQSIBBKgEAoAQKhBAj+A2nInhF0VUgMAAAAAElFTkSu\nQmCC",
      "text/plain": [
       "Plot with title \"Abnormal Likelihood Index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ALI(gaussian_total2, \"3\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in if (class(bn.fit) != \"bn.fit\") {:\n",
      "\"the condition has length > 1 and only the first element will be used\""
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>F1</th><th scope=col>F2</th><th scope=col>F3</th><th scope=col>F4</th><th scope=col>F5</th><th scope=col>F6</th><th scope=col>P7</th><th scope=col>L8</th><th scope=col>T9</th><th scope=col>F10</th><th scope=col>...</th><th scope=col>F14</th><th scope=col>L15</th><th scope=col>P16</th><th scope=col>F17</th><th scope=col>T18</th><th scope=col>F19</th><th scope=col>J20</th><th scope=col>T21</th><th scope=col>T22</th><th scope=col>R5</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>0.4950855</td><td>0.4940164</td><td>0.4924965</td><td>0.4975459</td><td>0.4927013</td><td>0.5202141</td><td>0.5614153</td><td>0.4868836</td><td>0.496151 </td><td>0.5213549</td><td>...      </td><td>0.48294  </td><td>0.5044016</td><td>0.1735043</td><td>0.518605 </td><td>0.538062 </td><td>0.5007837</td><td>0.6035154</td><td>0.4886673</td><td>0.5011232</td><td>0.4889572</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllllllllllllllllllllll}\n",
       " F1 & F2 & F3 & F4 & F5 & F6 & P7 & L8 & T9 & F10 & ... & F14 & L15 & P16 & F17 & T18 & F19 & J20 & T21 & T22 & R5\\\\\n",
       "\\hline\n",
       "\t 0.4950855 & 0.4940164 & 0.4924965 & 0.4975459 & 0.4927013 & 0.5202141 & 0.5614153 & 0.4868836 & 0.496151  & 0.5213549 & ...       & 0.48294   & 0.5044016 & 0.1735043 & 0.518605  & 0.538062  & 0.5007837 & 0.6035154 & 0.4886673 & 0.5011232 & 0.4889572\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "F1 | F2 | F3 | F4 | F5 | F6 | P7 | L8 | T9 | F10 | ... | F14 | L15 | P16 | F17 | T18 | F19 | J20 | T21 | T22 | R5 | \n",
       "|---|\n",
       "| 0.4950855 | 0.4940164 | 0.4924965 | 0.4975459 | 0.4927013 | 0.5202141 | 0.5614153 | 0.4868836 | 0.496151  | 0.5213549 | ...       | 0.48294   | 0.5044016 | 0.1735043 | 0.518605  | 0.538062  | 0.5007837 | 0.6035154 | 0.4886673 | 0.5011232 | 0.4889572 | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  F1        F2        F3        F4        F5        F6        P7       \n",
       "1 0.4950855 0.4940164 0.4924965 0.4975459 0.4927013 0.5202141 0.5614153\n",
       "  L8        T9       F10       ... F14     L15       P16       F17     \n",
       "1 0.4868836 0.496151 0.5213549 ... 0.48294 0.5044016 0.1735043 0.518605\n",
       "  T18      F19       J20       T21       T22       R5       \n",
       "1 0.538062 0.5007837 0.6035154 0.4886673 0.5011232 0.4889572"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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1B8HopSvHjxDcXnoSjFixffUHweilK8ePENxeehKMWLF99QfB6KUrx48Q3F56Eo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\n/wHJW/4+F0/LLgAAAABJRU5ErkJggg==",
      "text/plain": [
       "Plot with title \"Bayesian Contribution index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bci_3 = BCI(gaussian_total2, \"default3\", 161, 160)\n",
    "bci_3\n",
    "\n",
    "BCI_plot(bci_3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<span style=\"color:purple\"><font size=\"5\"><b>[IDV4] Given</b></font></span> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Fault Occured at 161\n"
     ]
    },
    {
     "data": {
      "image/png": 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qEECIQSIBBKgEAoAQKhBAiEEiAQSoBA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\nQmCC",
      "text/plain": [
       "Plot with title \"Abnormal Likelihood Index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ALI(gaussian_total1, \"4\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in if (class(bn.fit) != \"bn.fit\") {:\n",
      "\"the condition has length > 1 and only the first element will be used\""
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>F1</th><th scope=col>F2</th><th scope=col>F3</th><th scope=col>F4</th><th scope=col>F5</th><th scope=col>F6</th><th scope=col>P7</th><th scope=col>L8</th><th scope=col>T9</th><th scope=col>F10</th><th scope=col>...</th><th scope=col>F14</th><th scope=col>L15</th><th scope=col>P16</th><th scope=col>F17</th><th scope=col>T18</th><th scope=col>F19</th><th scope=col>J20</th><th scope=col>T21</th><th scope=col>T22</th><th scope=col>R5</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>0.495094 </td><td>0.4940361</td><td>0.4924913</td><td>0.4975459</td><td>0.4932333</td><td>0.5202141</td><td>0.5512181</td><td>0.4873194</td><td>0.5005331</td><td>0.5213549</td><td>...      </td><td>0.4831153</td><td>0.5061478</td><td>0.1699648</td><td>0.5135149</td><td>0.5023036</td><td>0.4950345</td><td>0.6067311</td><td>0.5274916</td><td>0.494311 </td><td>0.4889751</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllllllllllllllllllllll}\n",
       " F1 & F2 & F3 & F4 & F5 & F6 & P7 & L8 & T9 & F10 & ... & F14 & L15 & P16 & F17 & T18 & F19 & J20 & T21 & T22 & R5\\\\\n",
       "\\hline\n",
       "\t 0.495094  & 0.4940361 & 0.4924913 & 0.4975459 & 0.4932333 & 0.5202141 & 0.5512181 & 0.4873194 & 0.5005331 & 0.5213549 & ...       & 0.4831153 & 0.5061478 & 0.1699648 & 0.5135149 & 0.5023036 & 0.4950345 & 0.6067311 & 0.5274916 & 0.494311  & 0.4889751\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "F1 | F2 | F3 | F4 | F5 | F6 | P7 | L8 | T9 | F10 | ... | F14 | L15 | P16 | F17 | T18 | F19 | J20 | T21 | T22 | R5 | \n",
       "|---|\n",
       "| 0.495094  | 0.4940361 | 0.4924913 | 0.4975459 | 0.4932333 | 0.5202141 | 0.5512181 | 0.4873194 | 0.5005331 | 0.5213549 | ...       | 0.4831153 | 0.5061478 | 0.1699648 | 0.5135149 | 0.5023036 | 0.4950345 | 0.6067311 | 0.5274916 | 0.494311  | 0.4889751 | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  F1       F2        F3        F4        F5        F6        P7       \n",
       "1 0.495094 0.4940361 0.4924913 0.4975459 0.4932333 0.5202141 0.5512181\n",
       "  L8        T9        F10       ... F14       L15       P16       F17      \n",
       "1 0.4873194 0.5005331 0.5213549 ... 0.4831153 0.5061478 0.1699648 0.5135149\n",
       "  T18       F19       J20       T21       T22      R5       \n",
       "1 0.5023036 0.4950345 0.6067311 0.5274916 0.494311 0.4889751"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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hxQ9+PxU/2cW+G5r3xpY42+jHVR/tp+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\nRU5ErkJggg==",
      "text/plain": [
       "Plot with title \"Bayesian Contribution index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bci_4a = BCI(gaussian_total1, \"default4\", 161, 160)\n",
    "bci_4a\n",
    "\n",
    "BCI_plot(bci_4a)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<span style=\"color:green\"><font size=\"5\"><b>[IDV4] Obtained</b></font></span> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Fault Occured at 161\n"
     ]
    },
    {
     "data": {
      "image/png": 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qEECIQSIBBKgEAoAQKhBAiEEiAQSoBA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\nQmCC",
      "text/plain": [
       "Plot with title \"Abnormal Likelihood Index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ALI(gaussian_total2, \"4\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in if (class(bn.fit) != \"bn.fit\") {:\n",
      "\"the condition has length > 1 and only the first element will be used\""
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>F1</th><th scope=col>F2</th><th scope=col>F3</th><th scope=col>F4</th><th scope=col>F5</th><th scope=col>F6</th><th scope=col>P7</th><th scope=col>L8</th><th scope=col>T9</th><th scope=col>F10</th><th scope=col>...</th><th scope=col>F14</th><th scope=col>L15</th><th scope=col>P16</th><th scope=col>F17</th><th scope=col>T18</th><th scope=col>F19</th><th scope=col>J20</th><th scope=col>T21</th><th scope=col>T22</th><th scope=col>R5</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>0.4950855</td><td>0.4940164</td><td>0.4924965</td><td>0.4975459</td><td>0.4927013</td><td>0.5202141</td><td>0.5614153</td><td>0.4868836</td><td>0.496151 </td><td>0.5213549</td><td>...      </td><td>0.48294  </td><td>0.5044016</td><td>0.1735043</td><td>0.518605 </td><td>0.538062 </td><td>0.5007837</td><td>0.6035154</td><td>0.4886673</td><td>0.5011232</td><td>0.4889572</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllllllllllllllllllllll}\n",
       " F1 & F2 & F3 & F4 & F5 & F6 & P7 & L8 & T9 & F10 & ... & F14 & L15 & P16 & F17 & T18 & F19 & J20 & T21 & T22 & R5\\\\\n",
       "\\hline\n",
       "\t 0.4950855 & 0.4940164 & 0.4924965 & 0.4975459 & 0.4927013 & 0.5202141 & 0.5614153 & 0.4868836 & 0.496151  & 0.5213549 & ...       & 0.48294   & 0.5044016 & 0.1735043 & 0.518605  & 0.538062  & 0.5007837 & 0.6035154 & 0.4886673 & 0.5011232 & 0.4889572\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "F1 | F2 | F3 | F4 | F5 | F6 | P7 | L8 | T9 | F10 | ... | F14 | L15 | P16 | F17 | T18 | F19 | J20 | T21 | T22 | R5 | \n",
       "|---|\n",
       "| 0.4950855 | 0.4940164 | 0.4924965 | 0.4975459 | 0.4927013 | 0.5202141 | 0.5614153 | 0.4868836 | 0.496151  | 0.5213549 | ...       | 0.48294   | 0.5044016 | 0.1735043 | 0.518605  | 0.538062  | 0.5007837 | 0.6035154 | 0.4886673 | 0.5011232 | 0.4889572 | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  F1        F2        F3        F4        F5        F6        P7       \n",
       "1 0.4950855 0.4940164 0.4924965 0.4975459 0.4927013 0.5202141 0.5614153\n",
       "  L8        T9       F10       ... F14     L15       P16       F17     \n",
       "1 0.4868836 0.496151 0.5213549 ... 0.48294 0.5044016 0.1735043 0.518605\n",
       "  T18      F19       J20       T21       T22       R5       \n",
       "1 0.538062 0.5007837 0.6035154 0.4886673 0.5011232 0.4889572"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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1B8HopSvHjxDcXnoSjFixffUHweilK8ePENxeehKMWLF99QfB6KUrx48Q3F56Eo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\n/wHJW/4+F0/LLgAAAABJRU5ErkJggg==",
      "text/plain": [
       "Plot with title \"Bayesian Contribution index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bci_4 = BCI(gaussian_total2, \"default4\", 161, 160)\n",
    "bci_4\n",
    "\n",
    "BCI_plot(bci_4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<span style=\"color:purple\"><font size=\"5\"><b>[IDV5] Given</b></font></span> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Fault Occured at 161\n"
     ]
    },
    {
     "data": {
      "image/png": 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qEECIQSIBBKgEAoAQKhBAiEEiAQSoBA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\nQmCC",
      "text/plain": [
       "Plot with title \"Abnormal Likelihood Index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ALI(gaussian_total1, \"5\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in if (class(bn.fit) != \"bn.fit\") {:\n",
      "\"the condition has length > 1 and only the first element will be used\""
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>F1</th><th scope=col>F2</th><th scope=col>F3</th><th scope=col>F4</th><th scope=col>F5</th><th scope=col>F6</th><th scope=col>P7</th><th scope=col>L8</th><th scope=col>T9</th><th scope=col>F10</th><th scope=col>...</th><th scope=col>F14</th><th scope=col>L15</th><th scope=col>P16</th><th scope=col>F17</th><th scope=col>T18</th><th scope=col>F19</th><th scope=col>J20</th><th scope=col>T21</th><th scope=col>T22</th><th scope=col>R5</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>0.495094 </td><td>0.4940361</td><td>0.4924913</td><td>0.4975459</td><td>0.4932333</td><td>0.5202141</td><td>0.5512181</td><td>0.4873194</td><td>0.5005331</td><td>0.5213549</td><td>...      </td><td>0.4831153</td><td>0.5061478</td><td>0.1699648</td><td>0.5135149</td><td>0.5023036</td><td>0.4950345</td><td>0.6067311</td><td>0.5274916</td><td>0.494311 </td><td>0.4889751</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllllllllllllllllllllll}\n",
       " F1 & F2 & F3 & F4 & F5 & F6 & P7 & L8 & T9 & F10 & ... & F14 & L15 & P16 & F17 & T18 & F19 & J20 & T21 & T22 & R5\\\\\n",
       "\\hline\n",
       "\t 0.495094  & 0.4940361 & 0.4924913 & 0.4975459 & 0.4932333 & 0.5202141 & 0.5512181 & 0.4873194 & 0.5005331 & 0.5213549 & ...       & 0.4831153 & 0.5061478 & 0.1699648 & 0.5135149 & 0.5023036 & 0.4950345 & 0.6067311 & 0.5274916 & 0.494311  & 0.4889751\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "F1 | F2 | F3 | F4 | F5 | F6 | P7 | L8 | T9 | F10 | ... | F14 | L15 | P16 | F17 | T18 | F19 | J20 | T21 | T22 | R5 | \n",
       "|---|\n",
       "| 0.495094  | 0.4940361 | 0.4924913 | 0.4975459 | 0.4932333 | 0.5202141 | 0.5512181 | 0.4873194 | 0.5005331 | 0.5213549 | ...       | 0.4831153 | 0.5061478 | 0.1699648 | 0.5135149 | 0.5023036 | 0.4950345 | 0.6067311 | 0.5274916 | 0.494311  | 0.4889751 | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  F1       F2        F3        F4        F5        F6        P7       \n",
       "1 0.495094 0.4940361 0.4924913 0.4975459 0.4932333 0.5202141 0.5512181\n",
       "  L8        T9        F10       ... F14       L15       P16       F17      \n",
       "1 0.4873194 0.5005331 0.5213549 ... 0.4831153 0.5061478 0.1699648 0.5135149\n",
       "  T18       F19       J20       T21       T22      R5       \n",
       "1 0.5023036 0.4950345 0.6067311 0.5274916 0.494311 0.4889751"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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hxQ9+PxU/2cW+G5r3xpY42+jHVR/tp+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\nRU5ErkJggg==",
      "text/plain": [
       "Plot with title \"Bayesian Contribution index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bci_5a = BCI(gaussian_total1, \"default5\", 161, 160)\n",
    "bci_5a\n",
    "\n",
    "BCI_plot(bci_5a)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<span style=\"color:green\"><font size=\"5\"><b>[IDV5] Obtained</b></font></span> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Fault Occured at 161\n"
     ]
    },
    {
     "data": {
      "image/png": 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qEECIQSIBBKgEAoAQKhBAiEEiAQSoBA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\nQmCC",
      "text/plain": [
       "Plot with title \"Abnormal Likelihood Index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ALI(gaussian_total2, \"5\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in if (class(bn.fit) != \"bn.fit\") {:\n",
      "\"the condition has length > 1 and only the first element will be used\""
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>F1</th><th scope=col>F2</th><th scope=col>F3</th><th scope=col>F4</th><th scope=col>F5</th><th scope=col>F6</th><th scope=col>P7</th><th scope=col>L8</th><th scope=col>T9</th><th scope=col>F10</th><th scope=col>...</th><th scope=col>F14</th><th scope=col>L15</th><th scope=col>P16</th><th scope=col>F17</th><th scope=col>T18</th><th scope=col>F19</th><th scope=col>J20</th><th scope=col>T21</th><th scope=col>T22</th><th scope=col>R5</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>0.4950855</td><td>0.4940164</td><td>0.4924965</td><td>0.4975459</td><td>0.4927013</td><td>0.5202141</td><td>0.5614153</td><td>0.4868836</td><td>0.496151 </td><td>0.5213549</td><td>...      </td><td>0.48294  </td><td>0.5044016</td><td>0.1735043</td><td>0.518605 </td><td>0.538062 </td><td>0.5007837</td><td>0.6035154</td><td>0.4886673</td><td>0.5011232</td><td>0.4889572</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllllllllllllllllllllll}\n",
       " F1 & F2 & F3 & F4 & F5 & F6 & P7 & L8 & T9 & F10 & ... & F14 & L15 & P16 & F17 & T18 & F19 & J20 & T21 & T22 & R5\\\\\n",
       "\\hline\n",
       "\t 0.4950855 & 0.4940164 & 0.4924965 & 0.4975459 & 0.4927013 & 0.5202141 & 0.5614153 & 0.4868836 & 0.496151  & 0.5213549 & ...       & 0.48294   & 0.5044016 & 0.1735043 & 0.518605  & 0.538062  & 0.5007837 & 0.6035154 & 0.4886673 & 0.5011232 & 0.4889572\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "F1 | F2 | F3 | F4 | F5 | F6 | P7 | L8 | T9 | F10 | ... | F14 | L15 | P16 | F17 | T18 | F19 | J20 | T21 | T22 | R5 | \n",
       "|---|\n",
       "| 0.4950855 | 0.4940164 | 0.4924965 | 0.4975459 | 0.4927013 | 0.5202141 | 0.5614153 | 0.4868836 | 0.496151  | 0.5213549 | ...       | 0.48294   | 0.5044016 | 0.1735043 | 0.518605  | 0.538062  | 0.5007837 | 0.6035154 | 0.4886673 | 0.5011232 | 0.4889572 | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  F1        F2        F3        F4        F5        F6        P7       \n",
       "1 0.4950855 0.4940164 0.4924965 0.4975459 0.4927013 0.5202141 0.5614153\n",
       "  L8        T9       F10       ... F14     L15       P16       F17     \n",
       "1 0.4868836 0.496151 0.5213549 ... 0.48294 0.5044016 0.1735043 0.518605\n",
       "  T18      F19       J20       T21       T22       R5       \n",
       "1 0.538062 0.5007837 0.6035154 0.4886673 0.5011232 0.4889572"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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e3kuO/lKMohdVdN3XufqO6iLO3z7DW+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\n/wHJW/4+F0/LLgAAAABJRU5ErkJggg==",
      "text/plain": [
       "Plot with title \"Bayesian Contribution index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bci_5 = BCI(gaussian_total2, \"default5\", 161, 160)\n",
    "bci_5\n",
    "\n",
    "BCI_plot(bci_5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<span style=\"color:purple\"><font size=\"5\"><b>[IDV6] Given</b></font></span> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 191,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Fault Occured at 164\n"
     ]
    },
    {
     "data": {
      "image/png": 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VACBEIJEAglQCCUAIFQAgRCCRAIJUAg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\nAqEECIQSIBBKgEAoAQKhBAj+A54imffcYVl0AAAAAElFTkSuQmCC",
      "text/plain": [
       "Plot with title \"Abnormal Likelihood Index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ALI(gaussian_total1, \"6\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 230,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in if (class(bn.fit) != \"bn.fit\") {:\n",
      "\"the condition has length > 1 and only the first element will be used\""
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>F1</th><th scope=col>F2</th><th scope=col>F3</th><th scope=col>F4</th><th scope=col>F5</th><th scope=col>F6</th><th scope=col>P7</th><th scope=col>L8</th><th scope=col>T9</th><th scope=col>F10</th><th scope=col>...</th><th scope=col>F14</th><th scope=col>L15</th><th scope=col>P16</th><th scope=col>F17</th><th scope=col>T18</th><th scope=col>F19</th><th scope=col>J20</th><th scope=col>T21</th><th scope=col>T22</th><th scope=col>R5</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>0.9352415</td><td>0.7459943</td><td>0.883241 </td><td>0.8911428</td><td>1.003125 </td><td>1.003125 </td><td>1.002515 </td><td>1.003125 </td><td>1.003125 </td><td>0.965057 </td><td>...      </td><td>0.9532842</td><td>0.8539226</td><td>1.003125 </td><td>0.9578688</td><td>1.000568 </td><td>1.003125 </td><td>1.003125 </td><td>1.003125 </td><td>1.003125 </td><td>1.003125 </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllllllllllllllllllllll}\n",
       " F1 & F2 & F3 & F4 & F5 & F6 & P7 & L8 & T9 & F10 & ... & F14 & L15 & P16 & F17 & T18 & F19 & J20 & T21 & T22 & R5\\\\\n",
       "\\hline\n",
       "\t 0.9352415 & 0.7459943 & 0.883241  & 0.8911428 & 1.003125  & 1.003125  & 1.002515  & 1.003125  & 1.003125  & 0.965057  & ...       & 0.9532842 & 0.8539226 & 1.003125  & 0.9578688 & 1.000568  & 1.003125  & 1.003125  & 1.003125  & 1.003125  & 1.003125 \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "F1 | F2 | F3 | F4 | F5 | F6 | P7 | L8 | T9 | F10 | ... | F14 | L15 | P16 | F17 | T18 | F19 | J20 | T21 | T22 | R5 | \n",
       "|---|\n",
       "| 0.9352415 | 0.7459943 | 0.883241  | 0.8911428 | 1.003125  | 1.003125  | 1.002515  | 1.003125  | 1.003125  | 0.965057  | ...       | 0.9532842 | 0.8539226 | 1.003125  | 0.9578688 | 1.000568  | 1.003125  | 1.003125  | 1.003125  | 1.003125  | 1.003125  | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  F1        F2        F3       F4        F5       F6       P7       L8      \n",
       "1 0.9352415 0.7459943 0.883241 0.8911428 1.003125 1.003125 1.002515 1.003125\n",
       "  T9       F10      ... F14       L15       P16      F17       T18     \n",
       "1 1.003125 0.965057 ... 0.9532842 0.8539226 1.003125 0.9578688 1.000568\n",
       "  F19      J20      T21      T22      R5      \n",
       "1 1.003125 1.003125 1.003125 1.003125 1.003125"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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OmCoac/Rn0ahLL/FGW6YOjpj1Gfhh6h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",
      "text/plain": [
       "Plot with title \"Bayesian Contribution index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bci_6a = BCI(gaussian_total1, \"default6\", 161, 160)\n",
    "bci_6a\n",
    "\n",
    "BCI_plot(bci_6a)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<span style=\"color:green\"><font size=\"5\"><b>[IDV6] Obtained</b></font></span> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 193,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Fault Occured at 164\n"
     ]
    },
    {
     "data": {
      "image/png": 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VACBEIJEAglQCCUAIFQAgRCCRAIJUAg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\nAqEECIQSIBBKgEAoAQKhBAj+A54imffcYVl0AAAAAElFTkSuQmCC",
      "text/plain": [
       "Plot with title \"Abnormal Likelihood Index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ALI(gaussian_total2, \"6\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 194,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in if (class(bn.fit) != \"bn.fit\") {:\n",
      "\"the condition has length > 1 and only the first element will be used\""
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>F1</th><th scope=col>F2</th><th scope=col>F3</th><th scope=col>F4</th><th scope=col>F5</th><th scope=col>F6</th><th scope=col>P7</th><th scope=col>L8</th><th scope=col>T9</th><th scope=col>F10</th><th scope=col>...</th><th scope=col>F14</th><th scope=col>L15</th><th scope=col>P16</th><th scope=col>F17</th><th scope=col>T18</th><th scope=col>F19</th><th scope=col>J20</th><th scope=col>T21</th><th scope=col>T22</th><th scope=col>R5</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>0.1144812</td><td>0.9896574</td><td>0.993039 </td><td>0.1720046</td><td>1.003125 </td><td>1.003124 </td><td>1.00307  </td><td>1.003125 </td><td>0.9988059</td><td>0.1619668</td><td>...      </td><td>0.5194021</td><td>0.8902093</td><td>1.003125 </td><td>0.3923622</td><td>1.002883 </td><td>1.003125 </td><td>1.003125 </td><td>1.003125 </td><td>1.003125 </td><td>1.003125 </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllllllllllllllllllllll}\n",
       " F1 & F2 & F3 & F4 & F5 & F6 & P7 & L8 & T9 & F10 & ... & F14 & L15 & P16 & F17 & T18 & F19 & J20 & T21 & T22 & R5\\\\\n",
       "\\hline\n",
       "\t 0.1144812 & 0.9896574 & 0.993039  & 0.1720046 & 1.003125  & 1.003124  & 1.00307   & 1.003125  & 0.9988059 & 0.1619668 & ...       & 0.5194021 & 0.8902093 & 1.003125  & 0.3923622 & 1.002883  & 1.003125  & 1.003125  & 1.003125  & 1.003125  & 1.003125 \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "F1 | F2 | F3 | F4 | F5 | F6 | P7 | L8 | T9 | F10 | ... | F14 | L15 | P16 | F17 | T18 | F19 | J20 | T21 | T22 | R5 | \n",
       "|---|\n",
       "| 0.1144812 | 0.9896574 | 0.993039  | 0.1720046 | 1.003125  | 1.003124  | 1.00307   | 1.003125  | 0.9988059 | 0.1619668 | ...       | 0.5194021 | 0.8902093 | 1.003125  | 0.3923622 | 1.002883  | 1.003125  | 1.003125  | 1.003125  | 1.003125  | 1.003125  | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  F1        F2        F3       F4        F5       F6       P7      L8      \n",
       "1 0.1144812 0.9896574 0.993039 0.1720046 1.003125 1.003124 1.00307 1.003125\n",
       "  T9        F10       ... F14       L15       P16      F17       T18     \n",
       "1 0.9988059 0.1619668 ... 0.5194021 0.8902093 1.003125 0.3923622 1.002883\n",
       "  F19      J20      T21      T22      R5      \n",
       "1 1.003125 1.003125 1.003125 1.003125 1.003125"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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4WZRjgU5XxsRW5sYAjHjV4pzDTCoSjnYytyYwNDOG70SmGmEQ5FOR9bkRsbGMJx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\n",
      "text/plain": [
       "Plot with title \"Bayesian Contribution index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bci_6 = BCI(gaussian_total2, \"default6\", 161, 160)\n",
    "bci_6\n",
    "\n",
    "BCI_plot(bci_6)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<span style=\"color:purple\"><font size=\"5\"><b>[IDV7] Given</b></font></span> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Fault Occured at 161\n"
     ]
    },
    {
     "data": {
      "image/png": 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qEECIQSIBBKgEAoAQKhBAiEEiAQSoBA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\nQmCC",
      "text/plain": [
       "Plot with title \"Abnormal Likelihood Index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ALI(gaussian_total1, \"7\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in if (class(bn.fit) != \"bn.fit\") {:\n",
      "\"the condition has length > 1 and only the first element will be used\""
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>F1</th><th scope=col>F2</th><th scope=col>F3</th><th scope=col>F4</th><th scope=col>F5</th><th scope=col>F6</th><th scope=col>P7</th><th scope=col>L8</th><th scope=col>T9</th><th scope=col>F10</th><th scope=col>...</th><th scope=col>F14</th><th scope=col>L15</th><th scope=col>P16</th><th scope=col>F17</th><th scope=col>T18</th><th scope=col>F19</th><th scope=col>J20</th><th scope=col>T21</th><th scope=col>T22</th><th scope=col>R5</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>0.495094 </td><td>0.4940361</td><td>0.4924913</td><td>0.4975459</td><td>0.4932333</td><td>0.5202141</td><td>0.5512181</td><td>0.4873194</td><td>0.5005331</td><td>0.5213549</td><td>...      </td><td>0.4831153</td><td>0.5061478</td><td>0.1699648</td><td>0.5135149</td><td>0.5023036</td><td>0.4950345</td><td>0.6067311</td><td>0.5274916</td><td>0.494311 </td><td>0.4889751</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllllllllllllllllllllll}\n",
       " F1 & F2 & F3 & F4 & F5 & F6 & P7 & L8 & T9 & F10 & ... & F14 & L15 & P16 & F17 & T18 & F19 & J20 & T21 & T22 & R5\\\\\n",
       "\\hline\n",
       "\t 0.495094  & 0.4940361 & 0.4924913 & 0.4975459 & 0.4932333 & 0.5202141 & 0.5512181 & 0.4873194 & 0.5005331 & 0.5213549 & ...       & 0.4831153 & 0.5061478 & 0.1699648 & 0.5135149 & 0.5023036 & 0.4950345 & 0.6067311 & 0.5274916 & 0.494311  & 0.4889751\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "F1 | F2 | F3 | F4 | F5 | F6 | P7 | L8 | T9 | F10 | ... | F14 | L15 | P16 | F17 | T18 | F19 | J20 | T21 | T22 | R5 | \n",
       "|---|\n",
       "| 0.495094  | 0.4940361 | 0.4924913 | 0.4975459 | 0.4932333 | 0.5202141 | 0.5512181 | 0.4873194 | 0.5005331 | 0.5213549 | ...       | 0.4831153 | 0.5061478 | 0.1699648 | 0.5135149 | 0.5023036 | 0.4950345 | 0.6067311 | 0.5274916 | 0.494311  | 0.4889751 | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  F1       F2        F3        F4        F5        F6        P7       \n",
       "1 0.495094 0.4940361 0.4924913 0.4975459 0.4932333 0.5202141 0.5512181\n",
       "  L8        T9        F10       ... F14       L15       P16       F17      \n",
       "1 0.4873194 0.5005331 0.5213549 ... 0.4831153 0.5061478 0.1699648 0.5135149\n",
       "  T18       F19       J20       T21       T22      R5       \n",
       "1 0.5023036 0.4950345 0.6067311 0.5274916 0.494311 0.4889751"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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hxQ9+PxU/2cW+G5r3xpY42+jHVR/tp+\nKOj3iTdz3kXdj8e6R58pWFEW/kfnUy3tgTYn2V8nJ99+Pf/569vJcd/LUZRDYj0ec5/yxRp9\nYdGKsuxcfqqlPdD21chvm18ddH7cu1CUA2I9Hgtv1rp3U91zX2g4bSztgTpv2/z+evbckl++\nHffncmouyk91hqMoR9Q994WG08bSHijWL8XIPv0L1WSF4+verHXvpsrnPndbFRnNe73CWkaw\nosyd8jIrFDT+sMOjbtayoy/sc819rPgYXhblz7PJydfL3kNfK1BRfqr4THWPvrDPNfex4mPY\nFOWv54b8Pvu1eDfn5KhNqSg/Jj5TsNHHOj/7ZHMfKz7EQ2FdlD8XDfn17OTX7PJs8vWYd6Eo\nPyi+yAsBQSenMEVZT3wZ66JclOPXyeLncy4nJ8e8C0UpXlEeNT7W3AeLL2P3l2Ksfsj7w37W\nO9iUi68mPlfhp9u5oyk7OZ8rvgxFKb6F+FyxNmvdcx8svgxFKb6F+FyxNmvdcx8svgxFKb6F\n+FyxNmvdcx8svoxtUe445l0oSvGK8hijCTr3weLLUJTiW4jPFWuz1j33weLL+Fw/wii+1fhc\nsTZr3XMfLL4MRSm+hfhcsTZr3XMfLL4MRSm+hfhcsTZr3XMfLL4MRSm+hfhcsTZr3XMfLL4M\nRSm+hfhcsTZr3XMfLL4MRSm+hfhcsTZr3XMfLL4MRSm+hfhcsTZr3XMfLL4MRSm+hfhcsTZr\n3XMfLL4MRSm+hfhcsTZr3XMfLL4MRSm+hfhcsTZr3XMfLL4MRSm+hfhcsTZr3XMfLL4MRSm+\nhfhcsTZr3XMfLL4MRSm+hfhcsTZr3XMfLL4MRSm+hfhcsTZr3XMfLL4MRSm+hfhcsTZr3XMf\nLL4MRSm+hfhcsTZr3XMfLL4MRSm+hfhcsTZr3XMfLL4MRSm+hfhcsTZr3XMfLL4MRSm+hfhc\nsTZr3XMfLL4MRSm+hfhcsTZr3XMfLL4MRSm+hfhcsTZr3XMfLL4MRSm+hfhcsTZr3XMfLL4M\nRSm+hfhcsTZr3XMfLL4MRSm+hfhcsTZr3XMfLL6MtxflNDVARSleUR5jNEHnPlh8GYpSfAvx\nuWJt1rrnPlh8Ga8vymnX2IGKUryiPMZogs59sPgyXl+UN4pSfJj4XLE2a91zHyy+jDecej9M\nr/7MnHqLjxCfK9ZmrXvug8WX8ZbXKB+vp7dPilJ8gPhcsTZr3XMfLL6Mt72Z88/06l9FKf7j\n43PF2qx1z32w+DLe+K7341XiBcqZohT/DvG5Ym3Wuuc+WHwZb/540J2iFP/x8blibda65z5Y\nfBl+Mkd8C/G5Ym3Wuuc+WHwZRylKHw8S/8HxuWJt1rrnPlh8GYWKcudvkBEUa8rFVxOfK9Zm\nrXvug8WX4dRbfAvxuWJt1rrnPlh8GYpSfAvxuWJt1rrnPlh8GYpSfAvxuWJt1rrnPlh8GW8o\nysd/buc/5n11+/A0epyiFK8ojzGaoHMfLL6M1xfl387vxPg7dqCiFK8ojzGaoHMfLL6M1xfl\n7fTucXHh8W56M3agohSvKI8xmqBzHyy+jLf8Psq+iz0UpXhFeYzRBJ37YPFlKErxLcTnirVZ\n6577YPFlvOUX99479RYfJD5XrM1a99wHiy/DmzniW4jPFWuz1j33weLLeMPHg54ebue/ZG16\nvXpmOURRileUxxhN0LkPFl+GD5yLbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+\nV6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4sv\nQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zN\nWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GK\nbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfc\nB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+\nV6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4sv\nQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zN\nWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GK\nbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfc\nB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+\nV6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4sv\nQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zN\nWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GK\nbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfc\nB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+\nV6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4sv\nQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zN\nWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GK\nbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfc\nB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+\nV6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4sv4w1F+fd6ev2wuDQdHaOi\nFK8ojzGaoHMfLL6M1xfl3+nczfyiohT/wfG5Ym3Wuuc+WHwZry/Km+n9bPbv1bwpFaX4D47P\nFWuz1j33weLLeH1RLtvxv3lTKkrxHxyfK9ZmrXvug8WX8daifG7KW0Up/qPjc8XarHXPfbD4\nMl5flHfzU+9nj9MbRSn+g+Nzxdqsdc99sPgyXl+U/01X/fhnqijFf3B8rlibte65DxZfxhs+\nHvTf3dXywt8bRSn+Y+Nzxdqsdc99sPgyfOBcfAvxuWJt1rrnPlh8GYpSfAvxuWJt1rrnPlh8\nGUcpSq9Riv/g+FyxNmvdcx8svoxCRbnzN8gIijXl4quJzxVrs9Y998Hiy3DqLb6F+FyxNmvd\ncx8svgxFKb6F+FyxNmvdcx8svgxFKb6F+FyxNmvdcx8svow3FOXjP7fz3x90dfvwNHqcohSv\nKI8xmqBzHyy+jLf+mrWlv2MHKkrxivIYowk698Hiy3h9Ud5O7x4XFx7vlr+VcoiiFK8ojzGa\noHMfLL6MN//2oBcXeyhK8YryGKMJOvfB4stQlOJbiM8Va7PWPffB4st40284d+otPkh8rlib\nte65DxZfhjdzxLcQnyvWZq177oPFl/GGjwc9PdxezVvyevXMcoiiFK8ojzGaoHMfLL4MHzgX\n30J8rlibte65DxZfhqIU30J8rlibte65DxZfhqIU30J8rlibte65DxZfhqIU30J8rtKjP1AT\ncx8svgxFKb6F+FyxRi/+iPFlKErxLcTnijV68UeML0NRim8hPles0Ys/YnwZilJ8C/G5Yo1e\n/BHjy1CU4luIzxVr9OKPGF+GohTfQnyuWKMXf8T4MhSl+Bbic8UavfgjxpehKMW3EJ8r1ujF\nHzG+DEUpvoX4XLFGL/6I8WUoSvEtxOeKNXrxR4wvQ1GKbyE+V6zRiz9ifBmKUnwL8blijV78\nEePLUJTiW4jPFWv04o8YX4aiFN9CfK5Yoxd/xPgyFKX4FuJzxRq9+CPGl6EoxbcQnyvW6MUf\nMb4MRSm+hfhcsUYv/ojxZShK8S3E54o1evFHjC9DUYpvIT5XrNGLP2J8GYpSfAvxuWKNXvwR\n48tQlOJbiM8Va/TijxhfhqIU30J8rlijF3/E+DIUpfgW4nPFGr34I8aXoSjFtxCfK9boxR8x\nvgxFKb6F+FyxRi/+iPFlKErxLcTnijV68UeML0NRim8hPles0Ys/YnwZilJ8C/G5Yo1e/BHj\ny1CU4luIzxVr9OKPGF+GohTfQnyuWKMXf8T4MhSl+Bbic8UavfgjxpehKMW3EJ8r1ujFHzG+\nDEUpvon4Q8UcvfjjxZehKMWLF99QfBmKUrx48Q3Fl6EoxYsX31B8GYpSvHjxDcWXoSjFixff\nUHwZilK8ePENxZehKMWLF99QfBmKUrx48Q3Fl6EoxYsX31B8GYpSvHjxDcWXoSjFixffUHwZ\nilK8ePENxZehKMWLF99QfBmKUrx48Q3Fl6EoxYsX31B8GYpSvHjxDcWXoSjFixffUHwZilK8\nePENxZehKMWLF99QfBmKUrx48Q3Fl6EoxYsX31B8GYpSvHjxDcWXoSjFixffUHwZilK8ePEN\nxZehKMWLF99QfBmKUrx48Q3Fl6EoxYsX31B8GYpSvHjxDcWXoSjFixffUHwZilK8ePENxZeh\nKMWLF99QfBmKUrx48Q3Fl6EoxYsX31B8GYpSvHjxDcWXoSjFixffUHwZilK8ePENxZehKMWL\nF99QfBmKUrx48Q3Fl6EoxYsX31B8GYpSvHjxDcWX8YaifPzndvrs6vbhafQ4RSlevPjPWpR/\np1t/xw5UlOLFi/+sRXk7vXtcXHi8m96MHagoxYsX/1mLcjrtu9hDUYoXL15RKkrx4sUHiS/j\n9UV5M7136i1evPhY8WV4M0e8ePENxZfxho8HPT3cXs1b8nr1zHKIohQvXvynLcpDKUrx4sUr\nygRFKV68eEXpXW/x4sUHiS+jUFHu/A1ygg6Uebx48eI/SXwZ73DqDVA3RQmQoCgBEt7h16wB\n1O0dfjIHoG7v8GvWAOr2Dr89CKBuihIg4R1+zRpA3byZA5DwDr9mDaBuPnAOkKAoARIUJUCC\nogRIUJQACYoSIEFRAiQoSoAERQmQoCgBEhQlQIKiBEhQlAAJihIgQVECJChKgARFCZCgKAES\nFCVAQtSi3Pz/li2v3qf+D3G7x/93N53ejP//nXUP/3M9vX7IG85NYjjdw7u3Oyj+ITme1cF3\nj52bJm6wufj35vDJmd/q8WZ6df900MA3yzS/j9u++5j2Hz8bWuDdv9bqmOHl7c5L5wZDCzw4\nmKHl7R3O4PQPjGZwfXuHM7y8A3M5uL79h48v7+zFfhpc2BfD2Vmi3qUdOHx0665vsRzBIfvq\niOooyvvkjHSO/295YbQMOof/WfyZaMrd4TxkFN/jIQvajb9Lj2dz+OPm8lUif33p3+Xh/x4U\nvxn+1X8HDHyzTE+bwY0lz7rLOrDAO19dHTOyvN152d5gcIGHBjO4vH3DGV7f/tEMr2/vcIaX\nt38uh9e39/DE8s5299Pwwu4OZ2eJ+pe2//Dxrbu9zd8D99URxS3KzpW79Ix0Drib3s+X5/rA\nw6+fp/3fRNHsDucxOZzO9/+djyalc/zj9ObpeW8fMvr7zf+f+r/TPwfmz/+2s7/j8d1b3M23\n9MPg36F3mRaH303/Sd1ku6xDC9z96vqYkeXdnZf1DQYXeOAxNry8fcMZXt/+0Qyv7/BDfnB5\n9+dyeH174xPLu7jRdsLHF7b7oNku0cje3T98fOuujn9aHHDQvjqiGory6upvTlFeTV8GjMen\nj37x/eurjMMfEh328vj7A45fH7652VWi+Lb50wMmZ/8uNo08HNxZptv5c47H6W3iJttlHVzg\n7qqujxlZ3p1B74b2n7z2DH5sefuGM7y+/aMZXt/hh/zg8u7P5fD69sYnlnfx/e2Ejy/s9i46\nSzS2d/cPH9+6m6/PLxy0r46ohqK8P2Bn7x1w8DPKueQ/T93j/5n+ySjKu+m/t1g0tH0AAAeL\nSURBVNPrxP/zeef4m+ngedDe4es/78dPpbv5t8tnHIOP9f67SD7WF6NYXz3w4b5d1sEF7v4D\nsnvM2DPK5Z87N+hd4P7H2Mjy9g1neH37RzO8voMP+eHl3Z/L4fXtjU/9u9n5F/Y6/RRk9zuL\nJRrbuz2Hv7jUe/zT6snnAfvqiOIW5c5rEAcU5e5rFv8e9irf8tptsjg6x8//RU0X5ebw2+Wl\n8fbrHP/8n+cHwHjxLe/+6W56t7j6lDyT3nnG+ix91rK+xc18HodfIu5dpvHdt1N3076v9h+7\nc61/eV/My/YG/QvcO/ix5e0bzvD69o9meH2HHvIjy9szl4Pr2xufWN7tHSwm/PBanXWW6LCi\n3K7o4NbdeY3yoH11RI0W5X9Xg2cTPYffX6easnP81dVTTlEuXlh/WG+WQ46/WT0U0oevHib/\nJM9COuNdPMCSTyg3t/g7P/wmWlEOLO+Leek84epd4N7Bjy1v33CG17d/NMPrO/SQH1nenrkc\nXN/e+MTybu5gOeE5RbldooOKcnv48NZd/w1Wn/Y4YF8dUdyiHLuaOj7Vk3t5fxJPsrbH380X\nKF2UqS8MfnvxdOBh+FWj5TFzV+sPnlylJmfnNG781fu9W/z73DFPB549vVdRDi3vi3np3rxv\ngfsGP7q8g09we2/RP5rh9R16yI8s7/4Qhte3P358eddHrSY8oyg7S3TIg+eQnlwe/+/O1CV7\n4WiaLMrHVE++ocmmL/5lPnL8K96Kehxv1d0brB7riTf5X9zFfwe9mTPb3UlD9/H2ohxc3pch\niSrrG/zo8uYWZd/14fUdeMiPLe/+EIbnfnhHDS/v6qj1hKcePNvM7hIdUJTbw8e27vqfgpuX\nX3oPLRbln8Pfq5jNH7lP6Tt4fVGuNsb4q4id42+zi/Ih9SHQnqLMeA46m5+gHfTxoPXV68Pe\n9e4Z13j86trw8g5V08ACH6Uoh9e3fzTD6zvwkB9b3sGiPDx+NrS8N9P1UZsJH1/YTubOEqWL\ncnv46NZdHX+9+HzSQfvqiBosyr/pZ1jdw+/n855+ETFrOJ3vrz6plvpRm83FP8tTs9Hh7N79\nbf8ngPtvcDt/wStxZt+9xfXzqejT8D30zsv9fPR3wy/J910+vJlGlre/mgYXeHBRh5a3bzjD\n69s/muH1HRjO2PLuz+Xw+g78mza4vNfPSYug7YSPL+z2Lv4ednq8f/j41l0d/7j4yPtB++qI\nGizKm7ynfE9Xi5eSUm9LZw2ne16ziD/4c47r4Y8OZ/fur6fDP4K2ucF6SlY/0HBwtT4sDh/9\nQPLe1dV9DIwqryi7S7n8c2R5+6tpcIFfUZT7wxle3/7RDK/vwHDGlnd/LofXtzd+ZHmX33ro\nTvj4wm7v4qZnng46fHzrrr/+z3y6D9pXR9RgUea+iDj/+dK7xMcMXl+Us/9unx+JiSrbybu/\nmt6MF1nvGen4DTZT8vg8nNv0x882oeM/ed4/L6M/T/7WohxZ3oFqGlrgoxTl8PoOjGZwfQeG\nM7a8PXM5uL798SPL+3C1/Fbnb534RQHbIWcV5fbw8a27+fri5PuQfXVEUYsSIAxFCZCgKAES\nFCVAgqIESFCUAAmKEiBBUQIkKEqABEUJkKAoARIUJUCCogRIUJQACYoSIEFRAiQoSoAERQmQ\noCgBEhQlQIKiBEhQlAAJihIgQVECJChKgARFCZCgKAESFCVAgqIESFCUAAmKEiBBUQIkKEqA\nBEXJx/o5Od1cPp1c7B8wmQxdnXj08k481PhgJ5Ofq0u/Jyc931eUfDwPNT7Yt8nX1aWvm0sj\nFCUfwEOND3a5eR55MvmdPlxR8gE81PhoZ6tXJn9Ozp7/e/FlMjlZPLOcTC5PJ1+Wddj96vMz\nz83FZ99PJyffFwEXZ5PJWc+rnPBWipKPdjE5X/x5Pi/Mb5OFeRFOJl/mF+Z1+PKrk0WnLopy\ncW1x9fvyoO8f9zehWYqSD3eyfBQuem8y+TGb/VhdPLtcfXnnqye/Zr9O5l+YX7+YH3S5eFJ6\nMvk1P+h05J7gdRQlH+7rvPWeK277Vs6qEn9uLne/Oj+5vng+J19c/zKZl+nl8qrTbgpRlHy4\nX4sz57P5E8Jnvy++na0qcXF9+UffV5f/W5n37eTLr18f8RegeYqSj3f6/LTwcnXOfLbuvZ2i\n7P3qi6KcfTt5/vPkgHfOIZOi5ON9n3ybfVu+C3M+Of1+8ftlJfZ/df2/rYuvp16jpABFyceb\nP5s8XbzYuCy+3krcfHX+ymXnNcoXL0z6cCUFeFQRwPlk/RmheQ/+6nk1svPV5bveF8vv/Jhf\nfX5K+mV+Av/Du96UoSgJ4GKyfsv66+olx587Rbnz1fP5pS+znVcv569M/tgcA0emKIngZPNz\njM81ePZzc2Y9W/2x89Wvk5Nvm+/MfzJncr54B2fxkzl6kgIUJUCCogRIUJQACYoSIEFRAiQo\nSoAERQmQoCgBEhQlQIKiBEhQlAAJihIgQVECJChKgARFCZCgKAESFCVAgqIESFCUAAmKEiBB\nUQIkKEqABEUJkKAoARIUJUCCogRIUJQACYoSIEFRAiQoSoAERQmQ8H+ROHDp73QkaQAAAABJ\nRU5ErkJggg==",
      "text/plain": [
       "Plot with title \"Bayesian Contribution index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bci_7a = BCI(gaussian_total1, \"default7\", 161, 160)\n",
    "bci_7a\n",
    "\n",
    "BCI_plot(bci_7a)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<span style=\"color:green\"><font size=\"5\"><b>[IDV7] Obtained</b></font></span> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Fault Occured at 161\n"
     ]
    },
    {
     "data": {
      "image/png": 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qEECIQSIBBKgEAoAQKhBAiEEiAQSoBA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\nQmCC",
      "text/plain": [
       "Plot with title \"Abnormal Likelihood Index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ALI(gaussian_total2, \"7\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in if (class(bn.fit) != \"bn.fit\") {:\n",
      "\"the condition has length > 1 and only the first element will be used\""
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>F1</th><th scope=col>F2</th><th scope=col>F3</th><th scope=col>F4</th><th scope=col>F5</th><th scope=col>F6</th><th scope=col>P7</th><th scope=col>L8</th><th scope=col>T9</th><th scope=col>F10</th><th scope=col>...</th><th scope=col>F14</th><th scope=col>L15</th><th scope=col>P16</th><th scope=col>F17</th><th scope=col>T18</th><th scope=col>F19</th><th scope=col>J20</th><th scope=col>T21</th><th scope=col>T22</th><th scope=col>R5</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>0.4950855</td><td>0.4940164</td><td>0.4924965</td><td>0.4975459</td><td>0.4927013</td><td>0.5202141</td><td>0.5614153</td><td>0.4868836</td><td>0.496151 </td><td>0.5213549</td><td>...      </td><td>0.48294  </td><td>0.5044016</td><td>0.1735043</td><td>0.518605 </td><td>0.538062 </td><td>0.5007837</td><td>0.6035154</td><td>0.4886673</td><td>0.5011232</td><td>0.4889572</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllllllllllllllllllllll}\n",
       " F1 & F2 & F3 & F4 & F5 & F6 & P7 & L8 & T9 & F10 & ... & F14 & L15 & P16 & F17 & T18 & F19 & J20 & T21 & T22 & R5\\\\\n",
       "\\hline\n",
       "\t 0.4950855 & 0.4940164 & 0.4924965 & 0.4975459 & 0.4927013 & 0.5202141 & 0.5614153 & 0.4868836 & 0.496151  & 0.5213549 & ...       & 0.48294   & 0.5044016 & 0.1735043 & 0.518605  & 0.538062  & 0.5007837 & 0.6035154 & 0.4886673 & 0.5011232 & 0.4889572\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "F1 | F2 | F3 | F4 | F5 | F6 | P7 | L8 | T9 | F10 | ... | F14 | L15 | P16 | F17 | T18 | F19 | J20 | T21 | T22 | R5 | \n",
       "|---|\n",
       "| 0.4950855 | 0.4940164 | 0.4924965 | 0.4975459 | 0.4927013 | 0.5202141 | 0.5614153 | 0.4868836 | 0.496151  | 0.5213549 | ...       | 0.48294   | 0.5044016 | 0.1735043 | 0.518605  | 0.538062  | 0.5007837 | 0.6035154 | 0.4886673 | 0.5011232 | 0.4889572 | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  F1        F2        F3        F4        F5        F6        P7       \n",
       "1 0.4950855 0.4940164 0.4924965 0.4975459 0.4927013 0.5202141 0.5614153\n",
       "  L8        T9       F10       ... F14     L15       P16       F17     \n",
       "1 0.4868836 0.496151 0.5213549 ... 0.48294 0.5044016 0.1735043 0.518605\n",
       "  T18      F19       J20       T21       T22       R5       \n",
       "1 0.538062 0.5007837 0.6035154 0.4886673 0.5011232 0.4889572"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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e3kuO/lKMohdVdN3XufqO6iLO3z7DW+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\n/wHJW/4+F0/LLgAAAABJRU5ErkJggg==",
      "text/plain": [
       "Plot with title \"Bayesian Contribution index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bci_7 = BCI(gaussian_total2, \"default7\", 161, 160)\n",
    "bci_7\n",
    "\n",
    "BCI_plot(bci_7)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<span style=\"color:purple\"><font size=\"5\"><b>[IDV8] Given</b></font></span> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Fault Occured at 161\n"
     ]
    },
    {
     "data": {
      "image/png": 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qEECIQSIBBKgEAoAQKhBAiEEiAQSoBA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\nQmCC",
      "text/plain": [
       "Plot with title \"Abnormal Likelihood Index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ALI(gaussian_total1, \"8\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in if (class(bn.fit) != \"bn.fit\") {:\n",
      "\"the condition has length > 1 and only the first element will be used\""
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>F1</th><th scope=col>F2</th><th scope=col>F3</th><th scope=col>F4</th><th scope=col>F5</th><th scope=col>F6</th><th scope=col>P7</th><th scope=col>L8</th><th scope=col>T9</th><th scope=col>F10</th><th scope=col>...</th><th scope=col>F14</th><th scope=col>L15</th><th scope=col>P16</th><th scope=col>F17</th><th scope=col>T18</th><th scope=col>F19</th><th scope=col>J20</th><th scope=col>T21</th><th scope=col>T22</th><th scope=col>R5</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>0.495094 </td><td>0.4940361</td><td>0.4924913</td><td>0.4975459</td><td>0.4932333</td><td>0.5202141</td><td>0.5512181</td><td>0.4873194</td><td>0.5005331</td><td>0.5213549</td><td>...      </td><td>0.4831153</td><td>0.5061478</td><td>0.1699648</td><td>0.5135149</td><td>0.5023036</td><td>0.4950345</td><td>0.6067311</td><td>0.5274916</td><td>0.494311 </td><td>0.4889751</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllllllllllllllllllllll}\n",
       " F1 & F2 & F3 & F4 & F5 & F6 & P7 & L8 & T9 & F10 & ... & F14 & L15 & P16 & F17 & T18 & F19 & J20 & T21 & T22 & R5\\\\\n",
       "\\hline\n",
       "\t 0.495094  & 0.4940361 & 0.4924913 & 0.4975459 & 0.4932333 & 0.5202141 & 0.5512181 & 0.4873194 & 0.5005331 & 0.5213549 & ...       & 0.4831153 & 0.5061478 & 0.1699648 & 0.5135149 & 0.5023036 & 0.4950345 & 0.6067311 & 0.5274916 & 0.494311  & 0.4889751\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "F1 | F2 | F3 | F4 | F5 | F6 | P7 | L8 | T9 | F10 | ... | F14 | L15 | P16 | F17 | T18 | F19 | J20 | T21 | T22 | R5 | \n",
       "|---|\n",
       "| 0.495094  | 0.4940361 | 0.4924913 | 0.4975459 | 0.4932333 | 0.5202141 | 0.5512181 | 0.4873194 | 0.5005331 | 0.5213549 | ...       | 0.4831153 | 0.5061478 | 0.1699648 | 0.5135149 | 0.5023036 | 0.4950345 | 0.6067311 | 0.5274916 | 0.494311  | 0.4889751 | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  F1       F2        F3        F4        F5        F6        P7       \n",
       "1 0.495094 0.4940361 0.4924913 0.4975459 0.4932333 0.5202141 0.5512181\n",
       "  L8        T9        F10       ... F14       L15       P16       F17      \n",
       "1 0.4873194 0.5005331 0.5213549 ... 0.4831153 0.5061478 0.1699648 0.5135149\n",
       "  T18       F19       J20       T21       T22      R5       \n",
       "1 0.5023036 0.4950345 0.6067311 0.5274916 0.494311 0.4889751"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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hxQ9+PxU/2cW+G5r3xpY42+jHVR/tp+\nKOj3iTdz3kXdj8e6R58pWFEW/kfnUy3tgTYn2V8nJ99+Pf/569vJcd/LUZRDYj0ec5/yxRp9\nYdGKsuxcfqqlPdD21chvm18ddH7cu1CUA2I9Hgtv1rp3U91zX2g4bSztgTpv2/z+evbckl++\nHffncmouyk91hqMoR9Q994WG08bSHijWL8XIPv0L1WSF4+verHXvpsrnPndbFRnNe73CWkaw\nosyd8jIrFDT+sMOjbtayoy/sc819rPgYXhblz7PJydfL3kNfK1BRfqr4THWPvrDPNfex4mPY\nFOWv54b8Pvu1eDfn5KhNqSg/Jj5TsNHHOj/7ZHMfKz7EQ2FdlD8XDfn17OTX7PJs8vWYd6Eo\nPyi+yAsBQSenMEVZT3wZ66JclOPXyeLncy4nJ8e8C0UpXlEeNT7W3AeLL2P3l2Ksfsj7w37W\nO9iUi68mPlfhp9u5oyk7OZ8rvgxFKb6F+FyxNmvdcx8svgxFKb6F+FyxNmvdcx8svgxFKb6F\n+FyxNmvdcx8svoxtUe445l0oSvGK8hijCTr3weLLUJTiW4jPFWuz1j33weLL+Fw/wii+1fhc\nsTZr3XMfLL4MRSm+hfhcsTZr3XMfLL4MRSm+hfhcsTZr3XMfLL4MRSm+hfhcsTZr3XMfLL4M\nRSm+hfhcsTZr3XMfLL4MRSm+hfhcsTZr3XMfLL4MRSm+hfhcsTZr3XMfLL4MRSm+hfhcsTZr\n3XMfLL4MRSm+hfhcsTZr3XMfLL4MRSm+hfhcsTZr3XMfLL4MRSm+hfhcsTZr3XMfLL4MRSm+\nhfhcsTZr3XMfLL4MRSm+hfhcsTZr3XMfLL4MRSm+hfhcsTZr3XMfLL4MRSm+hfhcsTZr3XMf\nLL4MRSm+hfhcsTZr3XMfLL4MRSm+hfhcsTZr3XMfLL4MRSm+hfhcsTZr3XMfLL4MRSm+hfhc\nsTZr3XMfLL4MRSm+hfhcsTZr3XMfLL4MRSm+hfhcsTZr3XMfLL4MRSm+hfhcsTZr3XMfLL4M\nRSm+hfhcsTZr3XMfLL4MRSm+hfhcsTZr3XMfLL6MtxflNDVARSleUR5jNEHnPlh8GYpSfAvx\nuWJt1rrnPlh8Ga8vymnX2IGKUryiPMZogs59sPgyXl+UN4pSfJj4XLE2a91zHyy+jDecej9M\nr/7MnHqLjxCfK9ZmrXvug8WX8ZbXKB+vp7dPilJ8gPhcsTZr3XMfLL6Mt72Z88/06l9FKf7j\n43PF2qx1z32w+DLe+K7341XiBcqZohT/DvG5Ym3Wuuc+WHwZb/540J2iFP/x8blibda65z5Y\nfBl+Mkd8C/G5Ym3Wuuc+WHwZRylKHw8S/8HxuWJt1rrnPlh8GYWKcudvkBEUa8rFVxOfK9Zm\nrXvug8WX4dRbfAvxuWJt1rrnPlh8GYpSfAvxuWJt1rrnPlh8GYpSfAvxuWJt1rrnPlh8GW8o\nysd/buc/5n11+/A0epyiFK8ojzGaoHMfLL6M1xfl387vxPg7dqCiFK8ojzGaoHMfLL6M1xfl\n7fTucXHh8W56M3agohSvKI8xmqBzHyy+jLf8Psq+iz0UpXhFeYzRBJ37YPFlKErxLcTnirVZ\n6577YPFlvOUX99479RYfJD5XrM1a99wHiy/DmzniW4jPFWuz1j33weLLeMPHg54ebue/ZG16\nvXpmOURRileUxxhN0LkPFl+GD5yLbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+\nV6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4sv\nQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zN\nWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GK\nbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfc\nB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+\nV6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4sv\nQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zN\nWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GK\nbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfc\nB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+\nV6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4sv\nQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zN\nWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GK\nbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfc\nB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+\nV6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4sv\nQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zN\nWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GK\nbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfc\nB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+\nV6zNWvfcB4svQ1GKbyE+V6zNWvfcB4svQ1GKbyE+V6zNWvfcB4sv4w1F+fd6ev2wuDQdHaOi\nFK8ojzGaoHMfLL6M1xfl3+nczfyiohT/wfG5Ym3Wuuc+WHwZry/Km+n9bPbv1bwpFaX4D47P\nFWuz1j33weLLeH1RLtvxv3lTKkrxHxyfK9ZmrXvug8WX8daifG7KW0Up/qPjc8XarHXPfbD4\nMl5flHfzU+9nj9MbRSn+g+Nzxdqsdc99sPgyXl+U/01X/fhnqijFf3B8rlibte65DxZfxhs+\nHvTf3dXywt8bRSn+Y+Nzxdqsdc99sPgyfOBcfAvxuWJt1rrnPlh8GYpSfAvxuWJt1rrnPlh8\nGUcpSq9Riv/g+FyxNmvdcx8svoxCRbnzN8gIijXl4quJzxVrs9Y998Hiy3DqLb6F+FyxNmvd\ncx8svgxFKb6F+FyxNmvdcx8svgxFKb6F+FyxNmvdcx8svow3FOXjP7fz3x90dfvwNHqcohSv\nKI8xmqBzHyy+jLf+mrWlv2MHKkrxivIYowk698Hiy3h9Ud5O7x4XFx7vlr+VcoiiFK8ojzGa\noHMfLL6MN//2oBcXeyhK8YryGKMJOvfB4stQlOJbiM8Va7PWPffB4st40284d+otPkh8rlib\nte65DxZfhjdzxLcQnyvWZq177oPFl/GGjwc9PdxezVvyevXMcoiiFK8ojzGaoHMfLL4MHzgX\n30J8rlibte65DxZfhqIU30J8rlibte65DxZfhqIU30J8rlibte65DxZfhqIU30J8rtKjP1AT\ncx8svgxFKb6F+FyxRi/+iPFlKErxLcTnijV68UeML0NRim8hPles0Ys/YnwZilJ8C/G5Yo1e\n/BHjy1CU4luIzxVr9OKPGF+GohTfQnyuWKMXf8T4MhSl+Bbic8UavfgjxpehKMW3EJ8r1ujF\nHzG+DEUpvoX4XLFGL/6I8WUoSvEtxOeKNXrxR4wvQ1GKbyE+V6zRiz9ifBmKUnwL8blijV78\nEePLUJTiW4jPFWv04o8YX4aiFN9CfK5Yoxd/xPgyFKX4FuJzxRq9+CPGl6EoxbcQnyvW6MUf\nMb4MRSm+hfhcsUYv/ojxZShK8S3E54o1evFHjC9DUYpvIT5XrNGLP2J8GYpSfAvxuWKNXvwR\n48tQlOJbiM8Va/TijxhfhqIU30J8rlijF3/E+DIUpfgW4nPFGr34I8aXoSjFtxCfK9boxR8x\nvgxFKb6F+FyxRi/+iPFlKErxLcTnijV68UeML0NRim8hPles0Ys/YnwZilJ8C/G5Yo1e/BHj\ny1CU4luIzxVr9OKPGF+GohTfQnyuWKMXf8T4MhSl+Bbic8UavfgjxpehKMW3EJ8r1ujFHzG+\nDEUpvon4Q8UcvfjjxZehKMWLF99QfBmKUrx48Q3Fl6EoxYsX31B8GYpSvHjxDcWXoSjFixff\nUHwZilK8ePENxZehKMWLF99QfBmKUrx48Q3Fl6EoxYsX31B8GYpSvHjxDcWXoSjFixffUHwZ\nilK8ePENxZehKMWLF99QfBmKUrx48Q3Fl6EoxYsX31B8GYpSvHjxDcWXoSjFixffUHwZilK8\nePENxZehKMWLF99QfBmKUrx48Q3Fl6EoxYsX31B8GYpSvHjxDcWXoSjFixffUHwZilK8ePEN\nxZehKMWLF99QfBmKUrx48Q3Fl6EoxYsX31B8GYpSvHjxDcWXoSjFixffUHwZilK8ePENxZeh\nKMWLF99QfBmKUrx48Q3Fl6EoxYsX31B8GYpSvHjxDcWXoSjFixffUHwZilK8ePENxZehKMWL\nF99QfBmKUrx48Q3Fl6EoxYsX31B8GYpSvHjxDcWX8YaifPzndvrs6vbhafQ4RSlevPjPWpR/\np1t/xw5UlOLFi/+sRXk7vXtcXHi8m96MHagoxYsX/1mLcjrtu9hDUYoXL15RKkrx4sUHiS/j\n9UV5M7136i1evPhY8WV4M0e8ePENxZfxho8HPT3cXs1b8nr1zHKIohQvXvynLcpDKUrx4sUr\nygRFKV68eEXpXW/x4sUHiS+jUFHu/A1ygg6Uebx48eI/SXwZ73DqDVA3RQmQoCgBEt7h16wB\n1O0dfjIHoG7v8GvWAOr2Dr89CKBuihIg4R1+zRpA3byZA5DwDr9mDaBuPnAOkKAoARIUJUCC\nogRIUJQACYoSIEFRAiQoSoAERQmQoCgBEhQlQIKiBEhQlAAJihIgQVECJChKgARFCZCgKAES\nFCVAQtSi3Pz/li2v3qf+D3G7x/93N53ejP//nXUP/3M9vX7IG85NYjjdw7u3Oyj+ITme1cF3\nj52bJm6wufj35vDJmd/q8WZ6df900MA3yzS/j9u++5j2Hz8bWuDdv9bqmOHl7c5L5wZDCzw4\nmKHl7R3O4PQPjGZwfXuHM7y8A3M5uL79h48v7+zFfhpc2BfD2Vmi3qUdOHx0665vsRzBIfvq\niOooyvvkjHSO/295YbQMOof/WfyZaMrd4TxkFN/jIQvajb9Lj2dz+OPm8lUif33p3+Xh/x4U\nvxn+1X8HDHyzTE+bwY0lz7rLOrDAO19dHTOyvN152d5gcIGHBjO4vH3DGV7f/tEMr2/vcIaX\nt38uh9e39/DE8s5299Pwwu4OZ2eJ+pe2//Dxrbu9zd8D99URxS3KzpW79Ix0Drib3s+X5/rA\nw6+fp/3fRNHsDucxOZzO9/+djyalc/zj9ObpeW8fMvr7zf+f+r/TPwfmz/+2s7/j8d1b3M23\n9MPg36F3mRaH303/Sd1ku6xDC9z96vqYkeXdnZf1DQYXeOAxNry8fcMZXt/+0Qyv7/BDfnB5\n9+dyeH174xPLu7jRdsLHF7b7oNku0cje3T98fOuujn9aHHDQvjqiGory6upvTlFeTV8GjMen\nj37x/eurjMMfEh328vj7A45fH7652VWi+Lb50wMmZ/8uNo08HNxZptv5c47H6W3iJttlHVzg\n7qqujxlZ3p1B74b2n7z2DH5sefuGM7y+/aMZXt/hh/zg8u7P5fD69sYnlnfx/e2Ejy/s9i46\nSzS2d/cPH9+6m6/PLxy0r46ohqK8P2Bn7x1w8DPKueQ/T93j/5n+ySjKu+m/t1g0tH0AAAeL\nSURBVNPrxP/zeef4m+ngedDe4es/78dPpbv5t8tnHIOP9f67SD7WF6NYXz3w4b5d1sEF7v4D\nsnvM2DPK5Z87N+hd4P7H2Mjy9g1neH37RzO8voMP+eHl3Z/L4fXtjU/9u9n5F/Y6/RRk9zuL\nJRrbuz2Hv7jUe/zT6snnAfvqiOIW5c5rEAcU5e5rFv8e9irf8tptsjg6x8//RU0X5ebw2+Wl\n8fbrHP/8n+cHwHjxLe/+6W56t7j6lDyT3nnG+ix91rK+xc18HodfIu5dpvHdt1N3076v9h+7\nc61/eV/My/YG/QvcO/ix5e0bzvD69o9meH2HHvIjy9szl4Pr2xufWN7tHSwm/PBanXWW6LCi\n3K7o4NbdeY3yoH11RI0W5X9Xg2cTPYffX6easnP81dVTTlEuXlh/WG+WQ46/WT0U0oevHib/\nJM9COuNdPMCSTyg3t/g7P/wmWlEOLO+Leek84epd4N7Bjy1v33CG17d/NMPrO/SQH1nenrkc\nXN/e+MTybu5gOeE5RbldooOKcnv48NZd/w1Wn/Y4YF8dUdyiHLuaOj7Vk3t5fxJPsrbH380X\nKF2UqS8MfnvxdOBh+FWj5TFzV+sPnlylJmfnNG781fu9W/z73DFPB549vVdRDi3vi3np3rxv\ngfsGP7q8g09we2/RP5rh9R16yI8s7/4Qhte3P358eddHrSY8oyg7S3TIg+eQnlwe/+/O1CV7\n4WiaLMrHVE++ocmmL/5lPnL8K96Kehxv1d0brB7riTf5X9zFfwe9mTPb3UlD9/H2ohxc3pch\niSrrG/zo8uYWZd/14fUdeMiPLe/+EIbnfnhHDS/v6qj1hKcePNvM7hIdUJTbw8e27vqfgpuX\nX3oPLRbln8Pfq5jNH7lP6Tt4fVGuNsb4q4id42+zi/Ih9SHQnqLMeA46m5+gHfTxoPXV68Pe\n9e4Z13j86trw8g5V08ACH6Uoh9e3fzTD6zvwkB9b3sGiPDx+NrS8N9P1UZsJH1/YTubOEqWL\ncnv46NZdHX+9+HzSQfvqiBosyr/pZ1jdw+/n855+ETFrOJ3vrz6plvpRm83FP8tTs9Hh7N79\nbf8ngPtvcDt/wStxZt+9xfXzqejT8D30zsv9fPR3wy/J910+vJlGlre/mgYXeHBRh5a3bzjD\n69s/muH1HRjO2PLuz+Xw+g78mza4vNfPSYug7YSPL+z2Lv4ednq8f/j41l0d/7j4yPtB++qI\nGizKm7ynfE9Xi5eSUm9LZw2ne16ziD/4c47r4Y8OZ/fur6fDP4K2ucF6SlY/0HBwtT4sDh/9\nQPLe1dV9DIwqryi7S7n8c2R5+6tpcIFfUZT7wxle3/7RDK/vwHDGlnd/LofXtzd+ZHmX33ro\nTvj4wm7v4qZnng46fHzrrr/+z3y6D9pXR9RgUea+iDj/+dK7xMcMXl+Us/9unx+JiSrbybu/\nmt6MF1nvGen4DTZT8vg8nNv0x882oeM/ed4/L6M/T/7WohxZ3oFqGlrgoxTl8PoOjGZwfQeG\nM7a8PXM5uL798SPL+3C1/Fbnb534RQHbIWcV5fbw8a27+fri5PuQfXVEUYsSIAxFCZCgKAES\nFCVAgqIESFCUAAmKEiBBUQIkKEqABEUJkKAoARIUJUCCogRIUJQACYoSIEFRAiQoSoAERQmQ\noCgBEhQlQIKiBEhQlAAJihIgQVECJChKgARFCZCgKAESFCVAgqIESFCUAAmKEiBBUQIkKEqA\nBEXJx/o5Od1cPp1c7B8wmQxdnXj08k481PhgJ5Ofq0u/Jyc931eUfDwPNT7Yt8nX1aWvm0sj\nFCUfwEOND3a5eR55MvmdPlxR8gE81PhoZ6tXJn9Ozp7/e/FlMjlZPLOcTC5PJ1+Wddj96vMz\nz83FZ99PJyffFwEXZ5PJWc+rnPBWipKPdjE5X/x5Pi/Mb5OFeRFOJl/mF+Z1+PKrk0WnLopy\ncW1x9fvyoO8f9zehWYqSD3eyfBQuem8y+TGb/VhdPLtcfXnnqye/Zr9O5l+YX7+YH3S5eFJ6\nMvk1P+h05J7gdRQlH+7rvPWeK277Vs6qEn9uLne/Oj+5vng+J19c/zKZl+nl8qrTbgpRlHy4\nX4sz57P5E8Jnvy++na0qcXF9+UffV5f/W5n37eTLr18f8RegeYqSj3f6/LTwcnXOfLbuvZ2i\n7P3qi6KcfTt5/vPkgHfOIZOi5ON9n3ybfVu+C3M+Of1+8ftlJfZ/df2/rYuvp16jpABFyceb\nP5s8XbzYuCy+3krcfHX+ymXnNcoXL0z6cCUFeFQRwPlk/RmheQ/+6nk1svPV5bveF8vv/Jhf\nfX5K+mV+Av/Du96UoSgJ4GKyfsv66+olx587Rbnz1fP5pS+znVcv569M/tgcA0emKIngZPNz\njM81ePZzc2Y9W/2x89Wvk5Nvm+/MfzJncr54B2fxkzl6kgIUJUCCogRIUJQACYoSIEFRAiQo\nSoAERQmQoCgBEhQlQIKiBEhQlAAJihIgQVECJChKgARFCZCgKAESFCVAgqIESFCUAAmKEiBB\nUQIkKEqABEUJkKAoARIUJUCCogRIUJQACYoSIEFRAiQoSoAERQmQ8H+ROHDp73QkaQAAAABJ\nRU5ErkJggg==",
      "text/plain": [
       "Plot with title \"Bayesian Contribution index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bci_8a = BCI(gaussian_total1, \"default8\", 161, 160)\n",
    "bci_8a\n",
    "\n",
    "BCI_plot(bci_8a)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<span style=\"color:green\"><font size=\"5\"><b>[IDV8] Obtained</b></font></span> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Fault Occured at 161\n"
     ]
    },
    {
     "data": {
      "image/png": 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qEECIQSIBBKgEAoAQKhBAiEEiAQSoBA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\nQmCC",
      "text/plain": [
       "Plot with title \"Abnormal Likelihood Index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ALI(gaussian_total2, \"8\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in if (class(bn.fit) != \"bn.fit\") {:\n",
      "\"the condition has length > 1 and only the first element will be used\""
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>F1</th><th scope=col>F2</th><th scope=col>F3</th><th scope=col>F4</th><th scope=col>F5</th><th scope=col>F6</th><th scope=col>P7</th><th scope=col>L8</th><th scope=col>T9</th><th scope=col>F10</th><th scope=col>...</th><th scope=col>F14</th><th scope=col>L15</th><th scope=col>P16</th><th scope=col>F17</th><th scope=col>T18</th><th scope=col>F19</th><th scope=col>J20</th><th scope=col>T21</th><th scope=col>T22</th><th scope=col>R5</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>0.4950855</td><td>0.4940164</td><td>0.4924965</td><td>0.4975459</td><td>0.4927013</td><td>0.5202141</td><td>0.5614153</td><td>0.4868836</td><td>0.496151 </td><td>0.5213549</td><td>...      </td><td>0.48294  </td><td>0.5044016</td><td>0.1735043</td><td>0.518605 </td><td>0.538062 </td><td>0.5007837</td><td>0.6035154</td><td>0.4886673</td><td>0.5011232</td><td>0.4889572</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllllllllllllllllllllll}\n",
       " F1 & F2 & F3 & F4 & F5 & F6 & P7 & L8 & T9 & F10 & ... & F14 & L15 & P16 & F17 & T18 & F19 & J20 & T21 & T22 & R5\\\\\n",
       "\\hline\n",
       "\t 0.4950855 & 0.4940164 & 0.4924965 & 0.4975459 & 0.4927013 & 0.5202141 & 0.5614153 & 0.4868836 & 0.496151  & 0.5213549 & ...       & 0.48294   & 0.5044016 & 0.1735043 & 0.518605  & 0.538062  & 0.5007837 & 0.6035154 & 0.4886673 & 0.5011232 & 0.4889572\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "F1 | F2 | F3 | F4 | F5 | F6 | P7 | L8 | T9 | F10 | ... | F14 | L15 | P16 | F17 | T18 | F19 | J20 | T21 | T22 | R5 | \n",
       "|---|\n",
       "| 0.4950855 | 0.4940164 | 0.4924965 | 0.4975459 | 0.4927013 | 0.5202141 | 0.5614153 | 0.4868836 | 0.496151  | 0.5213549 | ...       | 0.48294   | 0.5044016 | 0.1735043 | 0.518605  | 0.538062  | 0.5007837 | 0.6035154 | 0.4886673 | 0.5011232 | 0.4889572 | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  F1        F2        F3        F4        F5        F6        P7       \n",
       "1 0.4950855 0.4940164 0.4924965 0.4975459 0.4927013 0.5202141 0.5614153\n",
       "  L8        T9       F10       ... F14     L15       P16       F17     \n",
       "1 0.4868836 0.496151 0.5213549 ... 0.48294 0.5044016 0.1735043 0.518605\n",
       "  T18      F19       J20       T21       T22       R5       \n",
       "1 0.538062 0.5007837 0.6035154 0.4886673 0.5011232 0.4889572"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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1B8HopSvHjxDcXnoSjFixffUHweilK8ePENxeehKMWLF99QfB6KUrx48Q3F56Eo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\n/wHJW/4+F0/LLgAAAABJRU5ErkJggg==",
      "text/plain": [
       "Plot with title \"Bayesian Contribution index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bci_8 = BCI(gaussian_total2, \"default8\", 161, 160)\n",
    "bci_8\n",
    "\n",
    "BCI_plot(bci_8)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<span style=\"color:purple\"><font size=\"5\"><b>[IDV9] Given</b></font></span> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Fault Occured at 161\n"
     ]
    },
    {
     "data": {
      "image/png": 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qEECIQSIBBKgEAoAQKhBAiEEiAQSoBA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\nQmCC",
      "text/plain": [
       "Plot with title \"Abnormal Likelihood Index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ALI(gaussian_total1, \"9\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in if (class(bn.fit) != \"bn.fit\") {:\n",
      "\"the condition has length > 1 and only the first element will be used\""
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>F1</th><th scope=col>F2</th><th scope=col>F3</th><th scope=col>F4</th><th scope=col>F5</th><th scope=col>F6</th><th scope=col>P7</th><th scope=col>L8</th><th scope=col>T9</th><th scope=col>F10</th><th scope=col>...</th><th scope=col>F14</th><th scope=col>L15</th><th scope=col>P16</th><th scope=col>F17</th><th scope=col>T18</th><th scope=col>F19</th><th scope=col>J20</th><th scope=col>T21</th><th scope=col>T22</th><th scope=col>R5</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>0.495094 </td><td>0.4940361</td><td>0.4924913</td><td>0.4975459</td><td>0.4932333</td><td>0.5202141</td><td>0.5512181</td><td>0.4873194</td><td>0.5005331</td><td>0.5213549</td><td>...      </td><td>0.4831153</td><td>0.5061478</td><td>0.1699648</td><td>0.5135149</td><td>0.5023036</td><td>0.4950345</td><td>0.6067311</td><td>0.5274916</td><td>0.494311 </td><td>0.4889751</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllllllllllllllllllllll}\n",
       " F1 & F2 & F3 & F4 & F5 & F6 & P7 & L8 & T9 & F10 & ... & F14 & L15 & P16 & F17 & T18 & F19 & J20 & T21 & T22 & R5\\\\\n",
       "\\hline\n",
       "\t 0.495094  & 0.4940361 & 0.4924913 & 0.4975459 & 0.4932333 & 0.5202141 & 0.5512181 & 0.4873194 & 0.5005331 & 0.5213549 & ...       & 0.4831153 & 0.5061478 & 0.1699648 & 0.5135149 & 0.5023036 & 0.4950345 & 0.6067311 & 0.5274916 & 0.494311  & 0.4889751\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "F1 | F2 | F3 | F4 | F5 | F6 | P7 | L8 | T9 | F10 | ... | F14 | L15 | P16 | F17 | T18 | F19 | J20 | T21 | T22 | R5 | \n",
       "|---|\n",
       "| 0.495094  | 0.4940361 | 0.4924913 | 0.4975459 | 0.4932333 | 0.5202141 | 0.5512181 | 0.4873194 | 0.5005331 | 0.5213549 | ...       | 0.4831153 | 0.5061478 | 0.1699648 | 0.5135149 | 0.5023036 | 0.4950345 | 0.6067311 | 0.5274916 | 0.494311  | 0.4889751 | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  F1       F2        F3        F4        F5        F6        P7       \n",
       "1 0.495094 0.4940361 0.4924913 0.4975459 0.4932333 0.5202141 0.5512181\n",
       "  L8        T9        F10       ... F14       L15       P16       F17      \n",
       "1 0.4873194 0.5005331 0.5213549 ... 0.4831153 0.5061478 0.1699648 0.5135149\n",
       "  T18       F19       J20       T21       T22      R5       \n",
       "1 0.5023036 0.4950345 0.6067311 0.5274916 0.494311 0.4889751"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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hxQ9+PxU/2cW+G5r3xpY42+jHVR/tp+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\nRU5ErkJggg==",
      "text/plain": [
       "Plot with title \"Bayesian Contribution index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bci_9a = BCI(gaussian_total1, \"default9\", 161, 160)\n",
    "bci_9a\n",
    "\n",
    "BCI_plot(bci_9a)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<span style=\"color:green\"><font size=\"5\"><b>[IDV9] Obtained</b></font></span> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Fault Occured at 161\n"
     ]
    },
    {
     "data": {
      "image/png": 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qEECIQSIBBKgEAoAQKhBAiEEiAQSoBA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\nQmCC",
      "text/plain": [
       "Plot with title \"Abnormal Likelihood Index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ALI(gaussian_total2, \"9\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in if (class(bn.fit) != \"bn.fit\") {:\n",
      "\"the condition has length > 1 and only the first element will be used\""
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>F1</th><th scope=col>F2</th><th scope=col>F3</th><th scope=col>F4</th><th scope=col>F5</th><th scope=col>F6</th><th scope=col>P7</th><th scope=col>L8</th><th scope=col>T9</th><th scope=col>F10</th><th scope=col>...</th><th scope=col>F14</th><th scope=col>L15</th><th scope=col>P16</th><th scope=col>F17</th><th scope=col>T18</th><th scope=col>F19</th><th scope=col>J20</th><th scope=col>T21</th><th scope=col>T22</th><th scope=col>R5</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>0.4950855</td><td>0.4940164</td><td>0.4924965</td><td>0.4975459</td><td>0.4927013</td><td>0.5202141</td><td>0.5614153</td><td>0.4868836</td><td>0.496151 </td><td>0.5213549</td><td>...      </td><td>0.48294  </td><td>0.5044016</td><td>0.1735043</td><td>0.518605 </td><td>0.538062 </td><td>0.5007837</td><td>0.6035154</td><td>0.4886673</td><td>0.5011232</td><td>0.4889572</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllllllllllllllllllllll}\n",
       " F1 & F2 & F3 & F4 & F5 & F6 & P7 & L8 & T9 & F10 & ... & F14 & L15 & P16 & F17 & T18 & F19 & J20 & T21 & T22 & R5\\\\\n",
       "\\hline\n",
       "\t 0.4950855 & 0.4940164 & 0.4924965 & 0.4975459 & 0.4927013 & 0.5202141 & 0.5614153 & 0.4868836 & 0.496151  & 0.5213549 & ...       & 0.48294   & 0.5044016 & 0.1735043 & 0.518605  & 0.538062  & 0.5007837 & 0.6035154 & 0.4886673 & 0.5011232 & 0.4889572\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "F1 | F2 | F3 | F4 | F5 | F6 | P7 | L8 | T9 | F10 | ... | F14 | L15 | P16 | F17 | T18 | F19 | J20 | T21 | T22 | R5 | \n",
       "|---|\n",
       "| 0.4950855 | 0.4940164 | 0.4924965 | 0.4975459 | 0.4927013 | 0.5202141 | 0.5614153 | 0.4868836 | 0.496151  | 0.5213549 | ...       | 0.48294   | 0.5044016 | 0.1735043 | 0.518605  | 0.538062  | 0.5007837 | 0.6035154 | 0.4886673 | 0.5011232 | 0.4889572 | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  F1        F2        F3        F4        F5        F6        P7       \n",
       "1 0.4950855 0.4940164 0.4924965 0.4975459 0.4927013 0.5202141 0.5614153\n",
       "  L8        T9       F10       ... F14     L15       P16       F17     \n",
       "1 0.4868836 0.496151 0.5213549 ... 0.48294 0.5044016 0.1735043 0.518605\n",
       "  T18      F19       J20       T21       T22       R5       \n",
       "1 0.538062 0.5007837 0.6035154 0.4886673 0.5011232 0.4889572"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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1B8HopSvHjxDcXnoSjFixffUHweilK8ePENxeehKMWLF99QfB6KUrx48Q3F56Eo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\n/wHJW/4+F0/LLgAAAABJRU5ErkJggg==",
      "text/plain": [
       "Plot with title \"Bayesian Contribution index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bci_9 = BCI(gaussian_total2, \"default9\", 161, 160)\n",
    "bci_9\n",
    "\n",
    "BCI_plot(bci_9)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<span style=\"color:purple\"><font size=\"5\"><b>[IDV10] Given</b></font></span> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Fault Occured at 161\n"
     ]
    },
    {
     "data": {
      "image/png": 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qEECIQSIBBKgEAoAQKhBAiEEiAQSoBA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\nQmCC",
      "text/plain": [
       "Plot with title \"Abnormal Likelihood Index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ALI(gaussian_total1, \"10\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in if (class(bn.fit) != \"bn.fit\") {:\n",
      "\"the condition has length > 1 and only the first element will be used\""
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>F1</th><th scope=col>F2</th><th scope=col>F3</th><th scope=col>F4</th><th scope=col>F5</th><th scope=col>F6</th><th scope=col>P7</th><th scope=col>L8</th><th scope=col>T9</th><th scope=col>F10</th><th scope=col>...</th><th scope=col>F14</th><th scope=col>L15</th><th scope=col>P16</th><th scope=col>F17</th><th scope=col>T18</th><th scope=col>F19</th><th scope=col>J20</th><th scope=col>T21</th><th scope=col>T22</th><th scope=col>R5</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>0.495094 </td><td>0.4940361</td><td>0.4924913</td><td>0.4975459</td><td>0.4932333</td><td>0.5202141</td><td>0.5512181</td><td>0.4873194</td><td>0.5005331</td><td>0.5213549</td><td>...      </td><td>0.4831153</td><td>0.5061478</td><td>0.1699648</td><td>0.5135149</td><td>0.5023036</td><td>0.4950345</td><td>0.6067311</td><td>0.5274916</td><td>0.494311 </td><td>0.4889751</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllllllllllllllllllllll}\n",
       " F1 & F2 & F3 & F4 & F5 & F6 & P7 & L8 & T9 & F10 & ... & F14 & L15 & P16 & F17 & T18 & F19 & J20 & T21 & T22 & R5\\\\\n",
       "\\hline\n",
       "\t 0.495094  & 0.4940361 & 0.4924913 & 0.4975459 & 0.4932333 & 0.5202141 & 0.5512181 & 0.4873194 & 0.5005331 & 0.5213549 & ...       & 0.4831153 & 0.5061478 & 0.1699648 & 0.5135149 & 0.5023036 & 0.4950345 & 0.6067311 & 0.5274916 & 0.494311  & 0.4889751\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "F1 | F2 | F3 | F4 | F5 | F6 | P7 | L8 | T9 | F10 | ... | F14 | L15 | P16 | F17 | T18 | F19 | J20 | T21 | T22 | R5 | \n",
       "|---|\n",
       "| 0.495094  | 0.4940361 | 0.4924913 | 0.4975459 | 0.4932333 | 0.5202141 | 0.5512181 | 0.4873194 | 0.5005331 | 0.5213549 | ...       | 0.4831153 | 0.5061478 | 0.1699648 | 0.5135149 | 0.5023036 | 0.4950345 | 0.6067311 | 0.5274916 | 0.494311  | 0.4889751 | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  F1       F2        F3        F4        F5        F6        P7       \n",
       "1 0.495094 0.4940361 0.4924913 0.4975459 0.4932333 0.5202141 0.5512181\n",
       "  L8        T9        F10       ... F14       L15       P16       F17      \n",
       "1 0.4873194 0.5005331 0.5213549 ... 0.4831153 0.5061478 0.1699648 0.5135149\n",
       "  T18       F19       J20       T21       T22      R5       \n",
       "1 0.5023036 0.4950345 0.6067311 0.5274916 0.494311 0.4889751"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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hxQ9+PxU/2cW+G5r3xpY42+jHVR/tp+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\nRU5ErkJggg==",
      "text/plain": [
       "Plot with title \"Bayesian Contribution index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bci_10a = BCI(gaussian_total1, \"default10\", 161, 160)\n",
    "bci_10a\n",
    "\n",
    "BCI_plot(bci_10a)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<span style=\"color:green\"><font size=\"5\"><b>[IDV10] Obtained</b></font></span> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Fault Occured at 161\n"
     ]
    },
    {
     "data": {
      "image/png": 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qEECIQSIBBKgEAoAQKhBAiEEiAQSoBA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\nQmCC",
      "text/plain": [
       "Plot with title \"Abnormal Likelihood Index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ALI(gaussian_total2, \"10\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in if (class(bn.fit) != \"bn.fit\") {:\n",
      "\"the condition has length > 1 and only the first element will be used\""
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>F1</th><th scope=col>F2</th><th scope=col>F3</th><th scope=col>F4</th><th scope=col>F5</th><th scope=col>F6</th><th scope=col>P7</th><th scope=col>L8</th><th scope=col>T9</th><th scope=col>F10</th><th scope=col>...</th><th scope=col>F14</th><th scope=col>L15</th><th scope=col>P16</th><th scope=col>F17</th><th scope=col>T18</th><th scope=col>F19</th><th scope=col>J20</th><th scope=col>T21</th><th scope=col>T22</th><th scope=col>R5</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>0.4950855</td><td>0.4940164</td><td>0.4924965</td><td>0.4975459</td><td>0.4927013</td><td>0.5202141</td><td>0.5614153</td><td>0.4868836</td><td>0.496151 </td><td>0.5213549</td><td>...      </td><td>0.48294  </td><td>0.5044016</td><td>0.1735043</td><td>0.518605 </td><td>0.538062 </td><td>0.5007837</td><td>0.6035154</td><td>0.4886673</td><td>0.5011232</td><td>0.4889572</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllllllllllllllllllllll}\n",
       " F1 & F2 & F3 & F4 & F5 & F6 & P7 & L8 & T9 & F10 & ... & F14 & L15 & P16 & F17 & T18 & F19 & J20 & T21 & T22 & R5\\\\\n",
       "\\hline\n",
       "\t 0.4950855 & 0.4940164 & 0.4924965 & 0.4975459 & 0.4927013 & 0.5202141 & 0.5614153 & 0.4868836 & 0.496151  & 0.5213549 & ...       & 0.48294   & 0.5044016 & 0.1735043 & 0.518605  & 0.538062  & 0.5007837 & 0.6035154 & 0.4886673 & 0.5011232 & 0.4889572\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "F1 | F2 | F3 | F4 | F5 | F6 | P7 | L8 | T9 | F10 | ... | F14 | L15 | P16 | F17 | T18 | F19 | J20 | T21 | T22 | R5 | \n",
       "|---|\n",
       "| 0.4950855 | 0.4940164 | 0.4924965 | 0.4975459 | 0.4927013 | 0.5202141 | 0.5614153 | 0.4868836 | 0.496151  | 0.5213549 | ...       | 0.48294   | 0.5044016 | 0.1735043 | 0.518605  | 0.538062  | 0.5007837 | 0.6035154 | 0.4886673 | 0.5011232 | 0.4889572 | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  F1        F2        F3        F4        F5        F6        P7       \n",
       "1 0.4950855 0.4940164 0.4924965 0.4975459 0.4927013 0.5202141 0.5614153\n",
       "  L8        T9       F10       ... F14     L15       P16       F17     \n",
       "1 0.4868836 0.496151 0.5213549 ... 0.48294 0.5044016 0.1735043 0.518605\n",
       "  T18      F19       J20       T21       T22       R5       \n",
       "1 0.538062 0.5007837 0.6035154 0.4886673 0.5011232 0.4889572"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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1B8HopSvHjxDcXnoSjFixffUHweilK8ePENxeehKMWLF99QfB6KUrx48Q3F56Eo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\n/wHJW/4+F0/LLgAAAABJRU5ErkJggg==",
      "text/plain": [
       "Plot with title \"Bayesian Contribution index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bci_10 = BCI(gaussian_total2, \"default10\", 161, 160)\n",
    "bci_10\n",
    "\n",
    "BCI_plot(bci_10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<span style=\"color:purple\"><font size=\"5\"><b>[IDV11] Given</b></font></span> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Fault Occured at 161\n"
     ]
    },
    {
     "data": {
      "image/png": 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qEECIQSIBBKgEAoAQKhBAiEEiAQSoBA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\nQmCC",
      "text/plain": [
       "Plot with title \"Abnormal Likelihood Index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ALI(gaussian_total1, \"11\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in if (class(bn.fit) != \"bn.fit\") {:\n",
      "\"the condition has length > 1 and only the first element will be used\""
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>F1</th><th scope=col>F2</th><th scope=col>F3</th><th scope=col>F4</th><th scope=col>F5</th><th scope=col>F6</th><th scope=col>P7</th><th scope=col>L8</th><th scope=col>T9</th><th scope=col>F10</th><th scope=col>...</th><th scope=col>F14</th><th scope=col>L15</th><th scope=col>P16</th><th scope=col>F17</th><th scope=col>T18</th><th scope=col>F19</th><th scope=col>J20</th><th scope=col>T21</th><th scope=col>T22</th><th scope=col>R5</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>0.495094 </td><td>0.4940361</td><td>0.4924913</td><td>0.4975459</td><td>0.4932333</td><td>0.5202141</td><td>0.5512181</td><td>0.4873194</td><td>0.5005331</td><td>0.5213549</td><td>...      </td><td>0.4831153</td><td>0.5061478</td><td>0.1699648</td><td>0.5135149</td><td>0.5023036</td><td>0.4950345</td><td>0.6067311</td><td>0.5274916</td><td>0.494311 </td><td>0.4889751</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllllllllllllllllllllll}\n",
       " F1 & F2 & F3 & F4 & F5 & F6 & P7 & L8 & T9 & F10 & ... & F14 & L15 & P16 & F17 & T18 & F19 & J20 & T21 & T22 & R5\\\\\n",
       "\\hline\n",
       "\t 0.495094  & 0.4940361 & 0.4924913 & 0.4975459 & 0.4932333 & 0.5202141 & 0.5512181 & 0.4873194 & 0.5005331 & 0.5213549 & ...       & 0.4831153 & 0.5061478 & 0.1699648 & 0.5135149 & 0.5023036 & 0.4950345 & 0.6067311 & 0.5274916 & 0.494311  & 0.4889751\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "F1 | F2 | F3 | F4 | F5 | F6 | P7 | L8 | T9 | F10 | ... | F14 | L15 | P16 | F17 | T18 | F19 | J20 | T21 | T22 | R5 | \n",
       "|---|\n",
       "| 0.495094  | 0.4940361 | 0.4924913 | 0.4975459 | 0.4932333 | 0.5202141 | 0.5512181 | 0.4873194 | 0.5005331 | 0.5213549 | ...       | 0.4831153 | 0.5061478 | 0.1699648 | 0.5135149 | 0.5023036 | 0.4950345 | 0.6067311 | 0.5274916 | 0.494311  | 0.4889751 | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  F1       F2        F3        F4        F5        F6        P7       \n",
       "1 0.495094 0.4940361 0.4924913 0.4975459 0.4932333 0.5202141 0.5512181\n",
       "  L8        T9        F10       ... F14       L15       P16       F17      \n",
       "1 0.4873194 0.5005331 0.5213549 ... 0.4831153 0.5061478 0.1699648 0.5135149\n",
       "  T18       F19       J20       T21       T22      R5       \n",
       "1 0.5023036 0.4950345 0.6067311 0.5274916 0.494311 0.4889751"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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hxQ9+PxU/2cW+G5r3xpY42+jHVR/tp+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\nRU5ErkJggg==",
      "text/plain": [
       "Plot with title \"Bayesian Contribution index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bci_11a = BCI(gaussian_total1, \"default11\", 161, 160)\n",
    "bci_11a\n",
    "\n",
    "BCI_plot(bci_11a)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<span style=\"color:green\"><font size=\"5\"><b>[IDV11] Obtained</b></font></span> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Fault Occured at 161\n"
     ]
    },
    {
     "data": {
      "image/png": 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qEECIQSIBBKgEAoAQKhBAiEEiAQSoBA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\nQmCC",
      "text/plain": [
       "Plot with title \"Abnormal Likelihood Index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ALI(gaussian_total2, \"11\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in if (class(bn.fit) != \"bn.fit\") {:\n",
      "\"the condition has length > 1 and only the first element will be used\""
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>F1</th><th scope=col>F2</th><th scope=col>F3</th><th scope=col>F4</th><th scope=col>F5</th><th scope=col>F6</th><th scope=col>P7</th><th scope=col>L8</th><th scope=col>T9</th><th scope=col>F10</th><th scope=col>...</th><th scope=col>F14</th><th scope=col>L15</th><th scope=col>P16</th><th scope=col>F17</th><th scope=col>T18</th><th scope=col>F19</th><th scope=col>J20</th><th scope=col>T21</th><th scope=col>T22</th><th scope=col>R5</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>0.4950855</td><td>0.4940164</td><td>0.4924965</td><td>0.4975459</td><td>0.4927013</td><td>0.5202141</td><td>0.5614153</td><td>0.4868836</td><td>0.496151 </td><td>0.5213549</td><td>...      </td><td>0.48294  </td><td>0.5044016</td><td>0.1735043</td><td>0.518605 </td><td>0.538062 </td><td>0.5007837</td><td>0.6035154</td><td>0.4886673</td><td>0.5011232</td><td>0.4889572</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllllllllllllllllllllll}\n",
       " F1 & F2 & F3 & F4 & F5 & F6 & P7 & L8 & T9 & F10 & ... & F14 & L15 & P16 & F17 & T18 & F19 & J20 & T21 & T22 & R5\\\\\n",
       "\\hline\n",
       "\t 0.4950855 & 0.4940164 & 0.4924965 & 0.4975459 & 0.4927013 & 0.5202141 & 0.5614153 & 0.4868836 & 0.496151  & 0.5213549 & ...       & 0.48294   & 0.5044016 & 0.1735043 & 0.518605  & 0.538062  & 0.5007837 & 0.6035154 & 0.4886673 & 0.5011232 & 0.4889572\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "F1 | F2 | F3 | F4 | F5 | F6 | P7 | L8 | T9 | F10 | ... | F14 | L15 | P16 | F17 | T18 | F19 | J20 | T21 | T22 | R5 | \n",
       "|---|\n",
       "| 0.4950855 | 0.4940164 | 0.4924965 | 0.4975459 | 0.4927013 | 0.5202141 | 0.5614153 | 0.4868836 | 0.496151  | 0.5213549 | ...       | 0.48294   | 0.5044016 | 0.1735043 | 0.518605  | 0.538062  | 0.5007837 | 0.6035154 | 0.4886673 | 0.5011232 | 0.4889572 | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  F1        F2        F3        F4        F5        F6        P7       \n",
       "1 0.4950855 0.4940164 0.4924965 0.4975459 0.4927013 0.5202141 0.5614153\n",
       "  L8        T9       F10       ... F14     L15       P16       F17     \n",
       "1 0.4868836 0.496151 0.5213549 ... 0.48294 0.5044016 0.1735043 0.518605\n",
       "  T18      F19       J20       T21       T22       R5       \n",
       "1 0.538062 0.5007837 0.6035154 0.4886673 0.5011232 0.4889572"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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e3kuO/lKMohdVdN3XufqO6iLO3z7DW+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\n/wHJW/4+F0/LLgAAAABJRU5ErkJggg==",
      "text/plain": [
       "Plot with title \"Bayesian Contribution index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bci_11 = BCI(gaussian_total2, \"default11\", 161, 160)\n",
    "bci_11\n",
    "\n",
    "BCI_plot(bci_11)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<span style=\"color:purple\"><font size=\"5\"><b>[IDV12] Given</b></font></span> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Fault Occured at 161\n"
     ]
    },
    {
     "data": {
      "image/png": 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qEECIQSIBBKgEAoAQKhBAiEEiAQSoBA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\nQmCC",
      "text/plain": [
       "Plot with title \"Abnormal Likelihood Index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ALI(gaussian_total1, \"12\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in if (class(bn.fit) != \"bn.fit\") {:\n",
      "\"the condition has length > 1 and only the first element will be used\""
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>F1</th><th scope=col>F2</th><th scope=col>F3</th><th scope=col>F4</th><th scope=col>F5</th><th scope=col>F6</th><th scope=col>P7</th><th scope=col>L8</th><th scope=col>T9</th><th scope=col>F10</th><th scope=col>...</th><th scope=col>F14</th><th scope=col>L15</th><th scope=col>P16</th><th scope=col>F17</th><th scope=col>T18</th><th scope=col>F19</th><th scope=col>J20</th><th scope=col>T21</th><th scope=col>T22</th><th scope=col>R5</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>0.495094 </td><td>0.4940361</td><td>0.4924913</td><td>0.4975459</td><td>0.4932333</td><td>0.5202141</td><td>0.5512181</td><td>0.4873194</td><td>0.5005331</td><td>0.5213549</td><td>...      </td><td>0.4831153</td><td>0.5061478</td><td>0.1699648</td><td>0.5135149</td><td>0.5023036</td><td>0.4950345</td><td>0.6067311</td><td>0.5274916</td><td>0.494311 </td><td>0.4889751</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllllllllllllllllllllll}\n",
       " F1 & F2 & F3 & F4 & F5 & F6 & P7 & L8 & T9 & F10 & ... & F14 & L15 & P16 & F17 & T18 & F19 & J20 & T21 & T22 & R5\\\\\n",
       "\\hline\n",
       "\t 0.495094  & 0.4940361 & 0.4924913 & 0.4975459 & 0.4932333 & 0.5202141 & 0.5512181 & 0.4873194 & 0.5005331 & 0.5213549 & ...       & 0.4831153 & 0.5061478 & 0.1699648 & 0.5135149 & 0.5023036 & 0.4950345 & 0.6067311 & 0.5274916 & 0.494311  & 0.4889751\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "F1 | F2 | F3 | F4 | F5 | F6 | P7 | L8 | T9 | F10 | ... | F14 | L15 | P16 | F17 | T18 | F19 | J20 | T21 | T22 | R5 | \n",
       "|---|\n",
       "| 0.495094  | 0.4940361 | 0.4924913 | 0.4975459 | 0.4932333 | 0.5202141 | 0.5512181 | 0.4873194 | 0.5005331 | 0.5213549 | ...       | 0.4831153 | 0.5061478 | 0.1699648 | 0.5135149 | 0.5023036 | 0.4950345 | 0.6067311 | 0.5274916 | 0.494311  | 0.4889751 | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  F1       F2        F3        F4        F5        F6        P7       \n",
       "1 0.495094 0.4940361 0.4924913 0.4975459 0.4932333 0.5202141 0.5512181\n",
       "  L8        T9        F10       ... F14       L15       P16       F17      \n",
       "1 0.4873194 0.5005331 0.5213549 ... 0.4831153 0.5061478 0.1699648 0.5135149\n",
       "  T18       F19       J20       T21       T22      R5       \n",
       "1 0.5023036 0.4950345 0.6067311 0.5274916 0.494311 0.4889751"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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hxQ9+PxU/2cW+G5r3xpY42+jHVR/tp+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\nRU5ErkJggg==",
      "text/plain": [
       "Plot with title \"Bayesian Contribution index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bci_12a = BCI(gaussian_total1, \"default12\", 161, 160)\n",
    "bci_12a\n",
    "\n",
    "BCI_plot(bci_12a)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<span style=\"color:green\"><font size=\"5\"><b>[IDV12] Obtained</b></font></span> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Fault Occured at 161\n"
     ]
    },
    {
     "data": {
      "image/png": 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qEECIQSIBBKgEAoAQKhBAiEEiAQSoBA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\nQmCC",
      "text/plain": [
       "Plot with title \"Abnormal Likelihood Index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ALI(gaussian_total2, \"12\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in if (class(bn.fit) != \"bn.fit\") {:\n",
      "\"the condition has length > 1 and only the first element will be used\""
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>F1</th><th scope=col>F2</th><th scope=col>F3</th><th scope=col>F4</th><th scope=col>F5</th><th scope=col>F6</th><th scope=col>P7</th><th scope=col>L8</th><th scope=col>T9</th><th scope=col>F10</th><th scope=col>...</th><th scope=col>F14</th><th scope=col>L15</th><th scope=col>P16</th><th scope=col>F17</th><th scope=col>T18</th><th scope=col>F19</th><th scope=col>J20</th><th scope=col>T21</th><th scope=col>T22</th><th scope=col>R5</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>0.4950855</td><td>0.4940164</td><td>0.4924965</td><td>0.4975459</td><td>0.4927013</td><td>0.5202141</td><td>0.5614153</td><td>0.4868836</td><td>0.496151 </td><td>0.5213549</td><td>...      </td><td>0.48294  </td><td>0.5044016</td><td>0.1735043</td><td>0.518605 </td><td>0.538062 </td><td>0.5007837</td><td>0.6035154</td><td>0.4886673</td><td>0.5011232</td><td>0.4889572</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllllllllllllllllllllll}\n",
       " F1 & F2 & F3 & F4 & F5 & F6 & P7 & L8 & T9 & F10 & ... & F14 & L15 & P16 & F17 & T18 & F19 & J20 & T21 & T22 & R5\\\\\n",
       "\\hline\n",
       "\t 0.4950855 & 0.4940164 & 0.4924965 & 0.4975459 & 0.4927013 & 0.5202141 & 0.5614153 & 0.4868836 & 0.496151  & 0.5213549 & ...       & 0.48294   & 0.5044016 & 0.1735043 & 0.518605  & 0.538062  & 0.5007837 & 0.6035154 & 0.4886673 & 0.5011232 & 0.4889572\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "F1 | F2 | F3 | F4 | F5 | F6 | P7 | L8 | T9 | F10 | ... | F14 | L15 | P16 | F17 | T18 | F19 | J20 | T21 | T22 | R5 | \n",
       "|---|\n",
       "| 0.4950855 | 0.4940164 | 0.4924965 | 0.4975459 | 0.4927013 | 0.5202141 | 0.5614153 | 0.4868836 | 0.496151  | 0.5213549 | ...       | 0.48294   | 0.5044016 | 0.1735043 | 0.518605  | 0.538062  | 0.5007837 | 0.6035154 | 0.4886673 | 0.5011232 | 0.4889572 | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  F1        F2        F3        F4        F5        F6        P7       \n",
       "1 0.4950855 0.4940164 0.4924965 0.4975459 0.4927013 0.5202141 0.5614153\n",
       "  L8        T9       F10       ... F14     L15       P16       F17     \n",
       "1 0.4868836 0.496151 0.5213549 ... 0.48294 0.5044016 0.1735043 0.518605\n",
       "  T18      F19       J20       T21       T22       R5       \n",
       "1 0.538062 0.5007837 0.6035154 0.4886673 0.5011232 0.4889572"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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1B8HopSvHjxDcXnoSjFixffUHweilK8ePENxeehKMWLF99QfB6KUrx48Q3F56Eo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\n/wHJW/4+F0/LLgAAAABJRU5ErkJggg==",
      "text/plain": [
       "Plot with title \"Bayesian Contribution index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bci_12 = BCI(gaussian_total2, \"default12\", 161, 160)\n",
    "bci_12\n",
    "\n",
    "BCI_plot(bci_12)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<span style=\"color:purple\"><font size=\"5\"><b>[IDV13] Given</b></font></span> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Fault Occured at 161\n"
     ]
    },
    {
     "data": {
      "image/png": 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qEECIQSIBBKgEAoAQKhBAiEEiAQSoBA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\nQmCC",
      "text/plain": [
       "Plot with title \"Abnormal Likelihood Index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ALI(gaussian_total1, \"13\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in if (class(bn.fit) != \"bn.fit\") {:\n",
      "\"the condition has length > 1 and only the first element will be used\""
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>F1</th><th scope=col>F2</th><th scope=col>F3</th><th scope=col>F4</th><th scope=col>F5</th><th scope=col>F6</th><th scope=col>P7</th><th scope=col>L8</th><th scope=col>T9</th><th scope=col>F10</th><th scope=col>...</th><th scope=col>F14</th><th scope=col>L15</th><th scope=col>P16</th><th scope=col>F17</th><th scope=col>T18</th><th scope=col>F19</th><th scope=col>J20</th><th scope=col>T21</th><th scope=col>T22</th><th scope=col>R5</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>0.495094 </td><td>0.4940361</td><td>0.4924913</td><td>0.4975459</td><td>0.4932333</td><td>0.5202141</td><td>0.5512181</td><td>0.4873194</td><td>0.5005331</td><td>0.5213549</td><td>...      </td><td>0.4831153</td><td>0.5061478</td><td>0.1699648</td><td>0.5135149</td><td>0.5023036</td><td>0.4950345</td><td>0.6067311</td><td>0.5274916</td><td>0.494311 </td><td>0.4889751</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllllllllllllllllllllll}\n",
       " F1 & F2 & F3 & F4 & F5 & F6 & P7 & L8 & T9 & F10 & ... & F14 & L15 & P16 & F17 & T18 & F19 & J20 & T21 & T22 & R5\\\\\n",
       "\\hline\n",
       "\t 0.495094  & 0.4940361 & 0.4924913 & 0.4975459 & 0.4932333 & 0.5202141 & 0.5512181 & 0.4873194 & 0.5005331 & 0.5213549 & ...       & 0.4831153 & 0.5061478 & 0.1699648 & 0.5135149 & 0.5023036 & 0.4950345 & 0.6067311 & 0.5274916 & 0.494311  & 0.4889751\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "F1 | F2 | F3 | F4 | F5 | F6 | P7 | L8 | T9 | F10 | ... | F14 | L15 | P16 | F17 | T18 | F19 | J20 | T21 | T22 | R5 | \n",
       "|---|\n",
       "| 0.495094  | 0.4940361 | 0.4924913 | 0.4975459 | 0.4932333 | 0.5202141 | 0.5512181 | 0.4873194 | 0.5005331 | 0.5213549 | ...       | 0.4831153 | 0.5061478 | 0.1699648 | 0.5135149 | 0.5023036 | 0.4950345 | 0.6067311 | 0.5274916 | 0.494311  | 0.4889751 | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  F1       F2        F3        F4        F5        F6        P7       \n",
       "1 0.495094 0.4940361 0.4924913 0.4975459 0.4932333 0.5202141 0.5512181\n",
       "  L8        T9        F10       ... F14       L15       P16       F17      \n",
       "1 0.4873194 0.5005331 0.5213549 ... 0.4831153 0.5061478 0.1699648 0.5135149\n",
       "  T18       F19       J20       T21       T22      R5       \n",
       "1 0.5023036 0.4950345 0.6067311 0.5274916 0.494311 0.4889751"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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hxQ9+PxU/2cW+G5r3xpY42+jHVR/tp+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\nRU5ErkJggg==",
      "text/plain": [
       "Plot with title \"Bayesian Contribution index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bci_13a = BCI(gaussian_total1, \"default13\", 161, 160)\n",
    "bci_13a\n",
    "\n",
    "BCI_plot(bci_13a)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<span style=\"color:green\"><font size=\"5\"><b>[IDV13] Obtained</b></font></span> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Fault Occured at 161\n"
     ]
    },
    {
     "data": {
      "image/png": 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qEECIQSIBBKgEAoAQKhBAiEEiAQSoBA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\nQmCC",
      "text/plain": [
       "Plot with title \"Abnormal Likelihood Index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ALI(gaussian_total2, \"13\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in if (class(bn.fit) != \"bn.fit\") {:\n",
      "\"the condition has length > 1 and only the first element will be used\""
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>F1</th><th scope=col>F2</th><th scope=col>F3</th><th scope=col>F4</th><th scope=col>F5</th><th scope=col>F6</th><th scope=col>P7</th><th scope=col>L8</th><th scope=col>T9</th><th scope=col>F10</th><th scope=col>...</th><th scope=col>F14</th><th scope=col>L15</th><th scope=col>P16</th><th scope=col>F17</th><th scope=col>T18</th><th scope=col>F19</th><th scope=col>J20</th><th scope=col>T21</th><th scope=col>T22</th><th scope=col>R5</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>0.4950855</td><td>0.4940164</td><td>0.4924965</td><td>0.4975459</td><td>0.4927013</td><td>0.5202141</td><td>0.5614153</td><td>0.4868836</td><td>0.496151 </td><td>0.5213549</td><td>...      </td><td>0.48294  </td><td>0.5044016</td><td>0.1735043</td><td>0.518605 </td><td>0.538062 </td><td>0.5007837</td><td>0.6035154</td><td>0.4886673</td><td>0.5011232</td><td>0.4889572</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllllllllllllllllllllll}\n",
       " F1 & F2 & F3 & F4 & F5 & F6 & P7 & L8 & T9 & F10 & ... & F14 & L15 & P16 & F17 & T18 & F19 & J20 & T21 & T22 & R5\\\\\n",
       "\\hline\n",
       "\t 0.4950855 & 0.4940164 & 0.4924965 & 0.4975459 & 0.4927013 & 0.5202141 & 0.5614153 & 0.4868836 & 0.496151  & 0.5213549 & ...       & 0.48294   & 0.5044016 & 0.1735043 & 0.518605  & 0.538062  & 0.5007837 & 0.6035154 & 0.4886673 & 0.5011232 & 0.4889572\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "F1 | F2 | F3 | F4 | F5 | F6 | P7 | L8 | T9 | F10 | ... | F14 | L15 | P16 | F17 | T18 | F19 | J20 | T21 | T22 | R5 | \n",
       "|---|\n",
       "| 0.4950855 | 0.4940164 | 0.4924965 | 0.4975459 | 0.4927013 | 0.5202141 | 0.5614153 | 0.4868836 | 0.496151  | 0.5213549 | ...       | 0.48294   | 0.5044016 | 0.1735043 | 0.518605  | 0.538062  | 0.5007837 | 0.6035154 | 0.4886673 | 0.5011232 | 0.4889572 | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  F1        F2        F3        F4        F5        F6        P7       \n",
       "1 0.4950855 0.4940164 0.4924965 0.4975459 0.4927013 0.5202141 0.5614153\n",
       "  L8        T9       F10       ... F14     L15       P16       F17     \n",
       "1 0.4868836 0.496151 0.5213549 ... 0.48294 0.5044016 0.1735043 0.518605\n",
       "  T18      F19       J20       T21       T22       R5       \n",
       "1 0.538062 0.5007837 0.6035154 0.4886673 0.5011232 0.4889572"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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1B8HopSvHjxDcXnoSjFixffUHweilK8ePENxeehKMWLF99QfB6KUrx48Q3F56Eo\nxYsX31B8Hu8oyqd/7qYvru8en0e3U5TixYv/W4vyz3Trz9iGilK8ePF/a1HeTe+fFhee7qe3\nYxsqSvHixf+tRTmd9l3soSjFixevKBWlePHiC4nP4+1FeTt9cOotXrz4suLz8GaOePHiG4rP\n4x0fD3p+vLuet+TN6shyiKIUL178X1uUh1KU4sWLV5QBRSlevHhF6V1v8eLFFxKfR6ai3PkO\nUoIOlLi9ePHi/5L4PD7g1BugbooSIKAoAQIf8GvWAOr2AT+ZA1C3D/g1awB1+4DfHgRQN0UJ\nEPiAX7MGUDdv5gAEPuDXrAHUzQfOAQKKEiCgKAECihIgoCgBAooSIKAoAQKKEiCgKAECihIg\noCgBAooSIKAoAQKKEiCgKAECihIgoCgBAooSIKAoAQKlFuXm/1u2vPoQ/Q9xu9v/dz+d3o7/\n/866m/++md48pu3ObbA73c279zso/jHcn9XG90+duwZ32Fz8c3v44Mzv9XQ7vX54PmjHN9M0\nf4y7vseY9m8/G5rg3W9rtc3w9HbHpXOHoQke3Jmh6e3dncHhH9ibwfnt3Z3h6R0Yy8H57d98\nfHpnr9bT4MS+2p2dKeqd2oHNR5fu+h7LPThkXR1RHUX5EI5IZ/v/lhdGy6Cz+e/F30FT7u7O\nY0LxPR0yod34+3h/Nps/bS5fB/nrS/8uN//3oPjN7l//d8COb6bpebNzY8mz7rQOTPDOratt\nRqa3Oy7bOwxO8NDODE5v3+4Mz2//3gzPb+/uDE9v/1gOz2/v5sH0znbX0/DE7u7OzhT1T23/\n5uNLd3ufPweuqyMqtyg7V+7jEelscD99mE/PzYGb37wM+79B0ezuzlO4O52v/zvfm0hn+6fp\n7fPL2j5k7x82/z/1f6e/D8yff7ezP+Px3Xvcz5f04+D30DtNi83vp/9Ed9lO69AEd29dbzMy\nvbvjsr7D4AQPPMeGp7dvd4bnt39vhud3+Ck/OL37Yzk8v73xwfQu7rQd8PGJ7T5ptlM0snb3\nNx9fuqvtnxcbHLSujqiGory+/pNSlNfT1wHj8fHWr75+c52w+WPQYa+3fzhg+/Xmm7tdB8W3\nzZ8eMDj7D7Fp5OHgzjTdzY85nqZ3wV220zo4wd1ZXW8zMr07O70b2n/y2rPzY9PbtzvD89u/\nN8PzO/yUH5ze/bEcnt/e+GB6F1/fDvj4xG4fojNFY2t3f/Pxpbu5fX7hoHV1RDUU5cMBK3tv\ng4OPKOfCf5662/8z/Z1QlPfTf++mN8H/+byz/e108Dxob/P13w/jp9Ld/LvlEcfgc73/IcLn\n+mIv1lcPfLpvp3Vwgrv/gOxuM3ZEufx75w69E9z/HBuZ3r7dGZ7f/r0Znt/Bp9OkgVgAAAcu\nSURBVPzw9O6P5fD89sZH/252/oW9iQ9Bdr+ymKKxtduz+atLvds/rw4+D1hXR1RuUe68BnFA\nUe6+ZvHvYa/yLa/dhcXR2X7+L2pclJvN75aXxtuvs/3LHy9PgPHiWz788/30fnH1OTyT3jli\nfRGftazvcTsfx+GXiHunaXz17dTdtO/W/m13rvVP76tx2d6hf4J7d35sevt2Z3h++/dmeH6H\nnvIj09szloPz2xsfTO/2ARYDfnitzjpTdFhRbmd0cOnuvEZ50Lo6okaL8r/rwbOJns0fbqKm\n7Gx/ff2cUpSLF9Yf14vlkO1vV0+FePPV0+Sf8Cyks7+LJ1h4QLm5x5/55relFeXA9L4al84B\nV+8E9+782PT27c7w/PbvzfD8Dj3lR6a3ZywH57c3PpjezQMsBzylKLdTdFBRbjcfXrrr72D1\naY8D1tURlVuUY1ej7aOe3Mv7HRxkbbe/n09QXJTRDYNfXhwOPA6/arTcZu56/cGT62hwdk7j\nxl+937vHvy8d83zg2dNHFeXQ9L4al+7d+ya4b+dHp3fwALf3Hv17Mzy/Q0/5kend34Xh+e2P\nH5/e9VarAU8oys4UHfLkOaQnl9v/uzN0YS8cTZNF+RT15DuabPrqX+Yjx7/hrain8VbdvcPq\nuR68yf/qIf476M2c2e5KGnqM9xfl4PS+DgmqrG/nR6c3tSj7rg/P78BTfmx693dheOyHV9Tw\n9K62Wg949OTZZnan6ICi3G4+tnTX/xTcvr7pI7RYlL8Pf69iNn/mPscP8PaiXC2M8VcRO9vf\nJRflY/Qh0J6iTDgGnc1P0A76eND66s1h73r37Nd4/Ora8PQOVdPABB+lKIfnt39vhud34Ck/\nNr2DRXl4/Gxoem+n6602Az4+sZ3MnSmKi3K7+ejSXW1/s/h80kHr6ogaLMo/8RFWd/OH+bjH\nLyIm7U7n66tPqkU/arO5+Ht5aja6O7sPf9f/CeD+O9zNX/AKzuy797h5ORV9Hn6E3nF5mO/9\n/fBL8n2XD2+mkentr6bBCR6c1KHp7dud4fnt35vh+R3YnbHp3R/L4fkd+DdtcHpvXpIWQdsB\nH5/Y7UP8Oez0eH/z8aW72v5p8ZH3g9bVETVYlLdph3zP14uXkqK3pZN2p3tes4g/+HOO690f\n3Z3dh7+ZDv8I2uYO6yFZ/UDDwdX6uNh89APJe1dXjzGwV2lF2Z3K5d8j09tfTYMT/Iai3N+d\n4fnt35vh+R3YnbHp3R/L4fntjR+Z3uWXHrsDPj6x24e47RmngzYfX7rr2/+ZD/dB6+qIGizK\n1BcR5z9feh98zODtRTn77+7lmRhU2U7ew/X0drzIes9Ix++wGZKnl925iz9+tgkd/8nz/nEZ\n/Xny9xblyPQOVNPQBB+lKIfnd2BvBud3YHfGprdnLAfntz9+ZHofr5df6nzXwS8K2O5yUlFu\nNx9fupvbFyffh6yrIyq1KAGKoSgBAooSIKAoAQKKEiCgKAECihIgoCgBAooSIKAoAQKKEiCg\nKAECihIgoCgBAooSIKAoAQKKEiCgKAECihIgoCgBAooSIKAoAQKKEiCgKAECihIgoCgBAooS\nIKAoAQKKEiCgKAECihIgoCgBAooSIKAo+Vw/J6eby6eTi/0NJpOhqxPPXj6Ipxqf7GTyc3Xp\ncnLS83VFyefzVOOTfZt8XV36urk0QlHyCTzV+GRXm+PIk8llvLmi5BN4qvHZzlavTP6cnL38\nefFlMjlZHFlOJlenky/LOuze+nLkubn44vvp5OT7IuDibDI563mVE95LUfLZLibni7/P54X5\nbbIwL8LJ5Mv8wrwOX986WXTqoigX1xZXvy83+v553wnNUpR8upPls3DRe5PJj9nsx+ri2dXq\n5p1bT37Nfp3Mb5hfv5hvdLU4KD2Z/JpvdDrySPA2ipJP93Xeei8Vt30rZ1WJPzeXu7fOT64v\nXs7JF9e/TOZlerW86rSbTBQln+7X4sz5bH5A+OLy4tvZqhIX15d/9d26/G9l3reTL79+fcY3\nQPMUJZ/v9OWw8Gp1zny27r2douy99VVRzr6dvPx9csA755BIUfL5vk++zb4t34U5n5x+v7h8\nXYn9t67/27r4euo1SjJQlHy++dHk6eLFxmXx9Vbi5tb5K5ed1yhfvTDpw5Vk4FlFAc4n688I\nzXvwV8+rkZ1bl+96Xyy/8mN+9eWQ9Mv8BP6Hd73JQ1FSgIvJ+i3rr6uXHH/uFOXOrefzS19m\nO69ezl+Z/LHZBo5MUVKCk83PMb7U4NnPzZn1bPXXzq1fJyffNl+Z/2TO5HzxDs7iJ3P0JBko\nSoCAogQIKEqAgKIECChKgICiBAgoSoCAogQIKEqAgKIECChKgICiBAgoSoCAogQIKEqAgKIE\nCChKgICiBAgoSoCAogQIKEqAgKIECChKgICiBAgoSoCAogQIKEqAgKIECChKgICiBAgoSoDA\n/wHJW/4+F0/LLgAAAABJRU5ErkJggg==",
      "text/plain": [
       "Plot with title \"Bayesian Contribution index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bci_13 = BCI(gaussian_total2, \"default13\", 161, 160)\n",
    "bci_13\n",
    "\n",
    "BCI_plot(bci_13)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<span style=\"color:purple\"><font size=\"5\"><b>[IDV14] Given</b></font></span> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Fault Occured at 161\n"
     ]
    },
    {
     "data": {
      "image/png": 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qEECIQSIBBKgEAoAQKhBAiEEiAQSoBA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\nQmCC",
      "text/plain": [
       "Plot with title \"Abnormal Likelihood Index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ALI(gaussian_total1, \"14\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in if (class(bn.fit) != \"bn.fit\") {:\n",
      "\"the condition has length > 1 and only the first element will be used\""
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>F1</th><th scope=col>F2</th><th scope=col>F3</th><th scope=col>F4</th><th scope=col>F5</th><th scope=col>F6</th><th scope=col>P7</th><th scope=col>L8</th><th scope=col>T9</th><th scope=col>F10</th><th scope=col>...</th><th scope=col>F14</th><th scope=col>L15</th><th scope=col>P16</th><th scope=col>F17</th><th scope=col>T18</th><th scope=col>F19</th><th scope=col>J20</th><th scope=col>T21</th><th scope=col>T22</th><th scope=col>R5</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>0.495094 </td><td>0.4940361</td><td>0.4924913</td><td>0.4975459</td><td>0.4932333</td><td>0.5202141</td><td>0.5512181</td><td>0.4873194</td><td>0.5005331</td><td>0.5213549</td><td>...      </td><td>0.4831153</td><td>0.5061478</td><td>0.1699648</td><td>0.5135149</td><td>0.5023036</td><td>0.4950345</td><td>0.6067311</td><td>0.5274916</td><td>0.494311 </td><td>0.4889751</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllllllllllllllllllllll}\n",
       " F1 & F2 & F3 & F4 & F5 & F6 & P7 & L8 & T9 & F10 & ... & F14 & L15 & P16 & F17 & T18 & F19 & J20 & T21 & T22 & R5\\\\\n",
       "\\hline\n",
       "\t 0.495094  & 0.4940361 & 0.4924913 & 0.4975459 & 0.4932333 & 0.5202141 & 0.5512181 & 0.4873194 & 0.5005331 & 0.5213549 & ...       & 0.4831153 & 0.5061478 & 0.1699648 & 0.5135149 & 0.5023036 & 0.4950345 & 0.6067311 & 0.5274916 & 0.494311  & 0.4889751\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "F1 | F2 | F3 | F4 | F5 | F6 | P7 | L8 | T9 | F10 | ... | F14 | L15 | P16 | F17 | T18 | F19 | J20 | T21 | T22 | R5 | \n",
       "|---|\n",
       "| 0.495094  | 0.4940361 | 0.4924913 | 0.4975459 | 0.4932333 | 0.5202141 | 0.5512181 | 0.4873194 | 0.5005331 | 0.5213549 | ...       | 0.4831153 | 0.5061478 | 0.1699648 | 0.5135149 | 0.5023036 | 0.4950345 | 0.6067311 | 0.5274916 | 0.494311  | 0.4889751 | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  F1       F2        F3        F4        F5        F6        P7       \n",
       "1 0.495094 0.4940361 0.4924913 0.4975459 0.4932333 0.5202141 0.5512181\n",
       "  L8        T9        F10       ... F14       L15       P16       F17      \n",
       "1 0.4873194 0.5005331 0.5213549 ... 0.4831153 0.5061478 0.1699648 0.5135149\n",
       "  T18       F19       J20       T21       T22      R5       \n",
       "1 0.5023036 0.4950345 0.6067311 0.5274916 0.494311 0.4889751"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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hxQ9+PxU/2cW+G5r3xpY42+jHVR/tp+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\nRU5ErkJggg==",
      "text/plain": [
       "Plot with title \"Bayesian Contribution index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bci_14a = BCI(gaussian_total1, \"default14\", 161, 160)\n",
    "bci_14a\n",
    "\n",
    "BCI_plot(bci_14a)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<span style=\"color:green\"><font size=\"5\"><b>[IDV14] Obtained</b></font></span> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Fault Occured at 161\n"
     ]
    },
    {
     "data": {
      "image/png": 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qEECIQSIBBKgEAoAQKhBAiEEiAQSoBA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\nQmCC",
      "text/plain": [
       "Plot with title \"Abnormal Likelihood Index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ALI(gaussian_total2, \"14\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in if (class(bn.fit) != \"bn.fit\") {:\n",
      "\"the condition has length > 1 and only the first element will be used\""
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>F1</th><th scope=col>F2</th><th scope=col>F3</th><th scope=col>F4</th><th scope=col>F5</th><th scope=col>F6</th><th scope=col>P7</th><th scope=col>L8</th><th scope=col>T9</th><th scope=col>F10</th><th scope=col>...</th><th scope=col>F14</th><th scope=col>L15</th><th scope=col>P16</th><th scope=col>F17</th><th scope=col>T18</th><th scope=col>F19</th><th scope=col>J20</th><th scope=col>T21</th><th scope=col>T22</th><th scope=col>R5</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>0.4950855</td><td>0.4940164</td><td>0.4924965</td><td>0.4975459</td><td>0.4927013</td><td>0.5202141</td><td>0.5614153</td><td>0.4868836</td><td>0.496151 </td><td>0.5213549</td><td>...      </td><td>0.48294  </td><td>0.5044016</td><td>0.1735043</td><td>0.518605 </td><td>0.538062 </td><td>0.5007837</td><td>0.6035154</td><td>0.4886673</td><td>0.5011232</td><td>0.4889572</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllllllllllllllllllllll}\n",
       " F1 & F2 & F3 & F4 & F5 & F6 & P7 & L8 & T9 & F10 & ... & F14 & L15 & P16 & F17 & T18 & F19 & J20 & T21 & T22 & R5\\\\\n",
       "\\hline\n",
       "\t 0.4950855 & 0.4940164 & 0.4924965 & 0.4975459 & 0.4927013 & 0.5202141 & 0.5614153 & 0.4868836 & 0.496151  & 0.5213549 & ...       & 0.48294   & 0.5044016 & 0.1735043 & 0.518605  & 0.538062  & 0.5007837 & 0.6035154 & 0.4886673 & 0.5011232 & 0.4889572\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "F1 | F2 | F3 | F4 | F5 | F6 | P7 | L8 | T9 | F10 | ... | F14 | L15 | P16 | F17 | T18 | F19 | J20 | T21 | T22 | R5 | \n",
       "|---|\n",
       "| 0.4950855 | 0.4940164 | 0.4924965 | 0.4975459 | 0.4927013 | 0.5202141 | 0.5614153 | 0.4868836 | 0.496151  | 0.5213549 | ...       | 0.48294   | 0.5044016 | 0.1735043 | 0.518605  | 0.538062  | 0.5007837 | 0.6035154 | 0.4886673 | 0.5011232 | 0.4889572 | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  F1        F2        F3        F4        F5        F6        P7       \n",
       "1 0.4950855 0.4940164 0.4924965 0.4975459 0.4927013 0.5202141 0.5614153\n",
       "  L8        T9       F10       ... F14     L15       P16       F17     \n",
       "1 0.4868836 0.496151 0.5213549 ... 0.48294 0.5044016 0.1735043 0.518605\n",
       "  T18      F19       J20       T21       T22       R5       \n",
       "1 0.538062 0.5007837 0.6035154 0.4886673 0.5011232 0.4889572"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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1B8HopSvHjxDcXnoSjFixffUHweilK8ePENxeehKMWLF99QfB6KUrx48Q3F56Eo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\n/wHJW/4+F0/LLgAAAABJRU5ErkJggg==",
      "text/plain": [
       "Plot with title \"Bayesian Contribution index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bci_14 = BCI(gaussian_total2, \"default14\", 161, 160)\n",
    "bci_14\n",
    "\n",
    "BCI_plot(bci_14)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<span style=\"color:purple\"><font size=\"5\"><b>[IDV15] Given</b></font></span> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Fault Occured at 161\n"
     ]
    },
    {
     "data": {
      "image/png": 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qEECIQSIBBKgEAoAQKhBAiEEiAQSoBA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\nQmCC",
      "text/plain": [
       "Plot with title \"Abnormal Likelihood Index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ALI(gaussian_total1, \"15\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in if (class(bn.fit) != \"bn.fit\") {:\n",
      "\"the condition has length > 1 and only the first element will be used\""
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>F1</th><th scope=col>F2</th><th scope=col>F3</th><th scope=col>F4</th><th scope=col>F5</th><th scope=col>F6</th><th scope=col>P7</th><th scope=col>L8</th><th scope=col>T9</th><th scope=col>F10</th><th scope=col>...</th><th scope=col>F14</th><th scope=col>L15</th><th scope=col>P16</th><th scope=col>F17</th><th scope=col>T18</th><th scope=col>F19</th><th scope=col>J20</th><th scope=col>T21</th><th scope=col>T22</th><th scope=col>R5</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>0.495094 </td><td>0.4940361</td><td>0.4924913</td><td>0.4975459</td><td>0.4932333</td><td>0.5202141</td><td>0.5512181</td><td>0.4873194</td><td>0.5005331</td><td>0.5213549</td><td>...      </td><td>0.4831153</td><td>0.5061478</td><td>0.1699648</td><td>0.5135149</td><td>0.5023036</td><td>0.4950345</td><td>0.6067311</td><td>0.5274916</td><td>0.494311 </td><td>0.4889751</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllllllllllllllllllllll}\n",
       " F1 & F2 & F3 & F4 & F5 & F6 & P7 & L8 & T9 & F10 & ... & F14 & L15 & P16 & F17 & T18 & F19 & J20 & T21 & T22 & R5\\\\\n",
       "\\hline\n",
       "\t 0.495094  & 0.4940361 & 0.4924913 & 0.4975459 & 0.4932333 & 0.5202141 & 0.5512181 & 0.4873194 & 0.5005331 & 0.5213549 & ...       & 0.4831153 & 0.5061478 & 0.1699648 & 0.5135149 & 0.5023036 & 0.4950345 & 0.6067311 & 0.5274916 & 0.494311  & 0.4889751\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "F1 | F2 | F3 | F4 | F5 | F6 | P7 | L8 | T9 | F10 | ... | F14 | L15 | P16 | F17 | T18 | F19 | J20 | T21 | T22 | R5 | \n",
       "|---|\n",
       "| 0.495094  | 0.4940361 | 0.4924913 | 0.4975459 | 0.4932333 | 0.5202141 | 0.5512181 | 0.4873194 | 0.5005331 | 0.5213549 | ...       | 0.4831153 | 0.5061478 | 0.1699648 | 0.5135149 | 0.5023036 | 0.4950345 | 0.6067311 | 0.5274916 | 0.494311  | 0.4889751 | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  F1       F2        F3        F4        F5        F6        P7       \n",
       "1 0.495094 0.4940361 0.4924913 0.4975459 0.4932333 0.5202141 0.5512181\n",
       "  L8        T9        F10       ... F14       L15       P16       F17      \n",
       "1 0.4873194 0.5005331 0.5213549 ... 0.4831153 0.5061478 0.1699648 0.5135149\n",
       "  T18       F19       J20       T21       T22      R5       \n",
       "1 0.5023036 0.4950345 0.6067311 0.5274916 0.494311 0.4889751"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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hxQ9+PxU/2cW+G5r3xpY42+jHVR/tp+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\nRU5ErkJggg==",
      "text/plain": [
       "Plot with title \"Bayesian Contribution index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bci_15a = BCI(gaussian_total1, \"default15\", 161, 160)\n",
    "bci_15a\n",
    "\n",
    "BCI_plot(bci_15a)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<span style=\"color:green\"><font size=\"5\"><b>[IDV15] Obtained</b></font></span> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Fault Occured at 161\n"
     ]
    },
    {
     "data": {
      "image/png": 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qEECIQSIBBKgEAoAQKhBAiEEiAQSoBA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\nQmCC",
      "text/plain": [
       "Plot with title \"Abnormal Likelihood Index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ALI(gaussian_total2, \"15\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in if (class(bn.fit) != \"bn.fit\") {:\n",
      "\"the condition has length > 1 and only the first element will be used\""
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>F1</th><th scope=col>F2</th><th scope=col>F3</th><th scope=col>F4</th><th scope=col>F5</th><th scope=col>F6</th><th scope=col>P7</th><th scope=col>L8</th><th scope=col>T9</th><th scope=col>F10</th><th scope=col>...</th><th scope=col>F14</th><th scope=col>L15</th><th scope=col>P16</th><th scope=col>F17</th><th scope=col>T18</th><th scope=col>F19</th><th scope=col>J20</th><th scope=col>T21</th><th scope=col>T22</th><th scope=col>R5</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>0.4950855</td><td>0.4940164</td><td>0.4924965</td><td>0.4975459</td><td>0.4927013</td><td>0.5202141</td><td>0.5614153</td><td>0.4868836</td><td>0.496151 </td><td>0.5213549</td><td>...      </td><td>0.48294  </td><td>0.5044016</td><td>0.1735043</td><td>0.518605 </td><td>0.538062 </td><td>0.5007837</td><td>0.6035154</td><td>0.4886673</td><td>0.5011232</td><td>0.4889572</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllllllllllllllllllllll}\n",
       " F1 & F2 & F3 & F4 & F5 & F6 & P7 & L8 & T9 & F10 & ... & F14 & L15 & P16 & F17 & T18 & F19 & J20 & T21 & T22 & R5\\\\\n",
       "\\hline\n",
       "\t 0.4950855 & 0.4940164 & 0.4924965 & 0.4975459 & 0.4927013 & 0.5202141 & 0.5614153 & 0.4868836 & 0.496151  & 0.5213549 & ...       & 0.48294   & 0.5044016 & 0.1735043 & 0.518605  & 0.538062  & 0.5007837 & 0.6035154 & 0.4886673 & 0.5011232 & 0.4889572\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "F1 | F2 | F3 | F4 | F5 | F6 | P7 | L8 | T9 | F10 | ... | F14 | L15 | P16 | F17 | T18 | F19 | J20 | T21 | T22 | R5 | \n",
       "|---|\n",
       "| 0.4950855 | 0.4940164 | 0.4924965 | 0.4975459 | 0.4927013 | 0.5202141 | 0.5614153 | 0.4868836 | 0.496151  | 0.5213549 | ...       | 0.48294   | 0.5044016 | 0.1735043 | 0.518605  | 0.538062  | 0.5007837 | 0.6035154 | 0.4886673 | 0.5011232 | 0.4889572 | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  F1        F2        F3        F4        F5        F6        P7       \n",
       "1 0.4950855 0.4940164 0.4924965 0.4975459 0.4927013 0.5202141 0.5614153\n",
       "  L8        T9       F10       ... F14     L15       P16       F17     \n",
       "1 0.4868836 0.496151 0.5213549 ... 0.48294 0.5044016 0.1735043 0.518605\n",
       "  T18      F19       J20       T21       T22       R5       \n",
       "1 0.538062 0.5007837 0.6035154 0.4886673 0.5011232 0.4889572"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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1B8HopSvHjxDcXnoSjFixffUHweilK8ePENxeehKMWLF99QfB6KUrx48Q3F56Eo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\n/wHJW/4+F0/LLgAAAABJRU5ErkJggg==",
      "text/plain": [
       "Plot with title \"Bayesian Contribution index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bci_15 = BCI(gaussian_total2, \"default15\", 161, 160)\n",
    "bci_15\n",
    "\n",
    "BCI_plot(bci_15)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<span style=\"color:purple\"><font size=\"5\"><b>[IDV16] Given</b></font></span> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Fault Occured at 161\n"
     ]
    },
    {
     "data": {
      "image/png": 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qEECIQSIBBKgEAoAQKhBAiEEiAQSoBA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\nQmCC",
      "text/plain": [
       "Plot with title \"Abnormal Likelihood Index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ALI(gaussian_total1, \"16\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in if (class(bn.fit) != \"bn.fit\") {:\n",
      "\"the condition has length > 1 and only the first element will be used\""
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>F1</th><th scope=col>F2</th><th scope=col>F3</th><th scope=col>F4</th><th scope=col>F5</th><th scope=col>F6</th><th scope=col>P7</th><th scope=col>L8</th><th scope=col>T9</th><th scope=col>F10</th><th scope=col>...</th><th scope=col>F14</th><th scope=col>L15</th><th scope=col>P16</th><th scope=col>F17</th><th scope=col>T18</th><th scope=col>F19</th><th scope=col>J20</th><th scope=col>T21</th><th scope=col>T22</th><th scope=col>R5</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>0.495094 </td><td>0.4940361</td><td>0.4924913</td><td>0.4975459</td><td>0.4932333</td><td>0.5202141</td><td>0.5512181</td><td>0.4873194</td><td>0.5005331</td><td>0.5213549</td><td>...      </td><td>0.4831153</td><td>0.5061478</td><td>0.1699648</td><td>0.5135149</td><td>0.5023036</td><td>0.4950345</td><td>0.6067311</td><td>0.5274916</td><td>0.494311 </td><td>0.4889751</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllllllllllllllllllllll}\n",
       " F1 & F2 & F3 & F4 & F5 & F6 & P7 & L8 & T9 & F10 & ... & F14 & L15 & P16 & F17 & T18 & F19 & J20 & T21 & T22 & R5\\\\\n",
       "\\hline\n",
       "\t 0.495094  & 0.4940361 & 0.4924913 & 0.4975459 & 0.4932333 & 0.5202141 & 0.5512181 & 0.4873194 & 0.5005331 & 0.5213549 & ...       & 0.4831153 & 0.5061478 & 0.1699648 & 0.5135149 & 0.5023036 & 0.4950345 & 0.6067311 & 0.5274916 & 0.494311  & 0.4889751\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "F1 | F2 | F3 | F4 | F5 | F6 | P7 | L8 | T9 | F10 | ... | F14 | L15 | P16 | F17 | T18 | F19 | J20 | T21 | T22 | R5 | \n",
       "|---|\n",
       "| 0.495094  | 0.4940361 | 0.4924913 | 0.4975459 | 0.4932333 | 0.5202141 | 0.5512181 | 0.4873194 | 0.5005331 | 0.5213549 | ...       | 0.4831153 | 0.5061478 | 0.1699648 | 0.5135149 | 0.5023036 | 0.4950345 | 0.6067311 | 0.5274916 | 0.494311  | 0.4889751 | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  F1       F2        F3        F4        F5        F6        P7       \n",
       "1 0.495094 0.4940361 0.4924913 0.4975459 0.4932333 0.5202141 0.5512181\n",
       "  L8        T9        F10       ... F14       L15       P16       F17      \n",
       "1 0.4873194 0.5005331 0.5213549 ... 0.4831153 0.5061478 0.1699648 0.5135149\n",
       "  T18       F19       J20       T21       T22      R5       \n",
       "1 0.5023036 0.4950345 0.6067311 0.5274916 0.494311 0.4889751"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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hxQ9+PxU/2cW+G5r3xpY42+jHVR/tp+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\nRU5ErkJggg==",
      "text/plain": [
       "Plot with title \"Bayesian Contribution index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bci_16a = BCI(gaussian_total1, \"default16\", 161, 160)\n",
    "bci_16a\n",
    "\n",
    "BCI_plot(bci_16a)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<span style=\"color:green\"><font size=\"5\"><b>[IDV16] Obtained</b></font></span> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Fault Occured at 161\n"
     ]
    },
    {
     "data": {
      "image/png": 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qEECIQSIBBKgEAoAQKhBAiEEiAQSoBA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\nQmCC",
      "text/plain": [
       "Plot with title \"Abnormal Likelihood Index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ALI(gaussian_total2, \"16\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in if (class(bn.fit) != \"bn.fit\") {:\n",
      "\"the condition has length > 1 and only the first element will be used\""
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>F1</th><th scope=col>F2</th><th scope=col>F3</th><th scope=col>F4</th><th scope=col>F5</th><th scope=col>F6</th><th scope=col>P7</th><th scope=col>L8</th><th scope=col>T9</th><th scope=col>F10</th><th scope=col>...</th><th scope=col>F14</th><th scope=col>L15</th><th scope=col>P16</th><th scope=col>F17</th><th scope=col>T18</th><th scope=col>F19</th><th scope=col>J20</th><th scope=col>T21</th><th scope=col>T22</th><th scope=col>R5</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>0.4950855</td><td>0.4940164</td><td>0.4924965</td><td>0.4975459</td><td>0.4927013</td><td>0.5202141</td><td>0.5614153</td><td>0.4868836</td><td>0.496151 </td><td>0.5213549</td><td>...      </td><td>0.48294  </td><td>0.5044016</td><td>0.1735043</td><td>0.518605 </td><td>0.538062 </td><td>0.5007837</td><td>0.6035154</td><td>0.4886673</td><td>0.5011232</td><td>0.4889572</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllllllllllllllllllllll}\n",
       " F1 & F2 & F3 & F4 & F5 & F6 & P7 & L8 & T9 & F10 & ... & F14 & L15 & P16 & F17 & T18 & F19 & J20 & T21 & T22 & R5\\\\\n",
       "\\hline\n",
       "\t 0.4950855 & 0.4940164 & 0.4924965 & 0.4975459 & 0.4927013 & 0.5202141 & 0.5614153 & 0.4868836 & 0.496151  & 0.5213549 & ...       & 0.48294   & 0.5044016 & 0.1735043 & 0.518605  & 0.538062  & 0.5007837 & 0.6035154 & 0.4886673 & 0.5011232 & 0.4889572\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "F1 | F2 | F3 | F4 | F5 | F6 | P7 | L8 | T9 | F10 | ... | F14 | L15 | P16 | F17 | T18 | F19 | J20 | T21 | T22 | R5 | \n",
       "|---|\n",
       "| 0.4950855 | 0.4940164 | 0.4924965 | 0.4975459 | 0.4927013 | 0.5202141 | 0.5614153 | 0.4868836 | 0.496151  | 0.5213549 | ...       | 0.48294   | 0.5044016 | 0.1735043 | 0.518605  | 0.538062  | 0.5007837 | 0.6035154 | 0.4886673 | 0.5011232 | 0.4889572 | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  F1        F2        F3        F4        F5        F6        P7       \n",
       "1 0.4950855 0.4940164 0.4924965 0.4975459 0.4927013 0.5202141 0.5614153\n",
       "  L8        T9       F10       ... F14     L15       P16       F17     \n",
       "1 0.4868836 0.496151 0.5213549 ... 0.48294 0.5044016 0.1735043 0.518605\n",
       "  T18      F19       J20       T21       T22       R5       \n",
       "1 0.538062 0.5007837 0.6035154 0.4886673 0.5011232 0.4889572"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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e3kuO/lKMohdVdN3XufqO6iLO3z7DW+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\n/wHJW/4+F0/LLgAAAABJRU5ErkJggg==",
      "text/plain": [
       "Plot with title \"Bayesian Contribution index\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bci_16 = BCI(gaussian_total2, \"default16\", 161, 160)\n",
    "bci_16\n",
    "\n",
    "BCI_plot(bci_16)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "R",
   "language": "R",
   "name": "ir"
  },
  "language_info": {
   "codemirror_mode": "r",
   "file_extension": ".r",
   "mimetype": "text/x-r-source",
   "name": "R",
   "pygments_lexer": "r",
   "version": "3.4.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
